RoleMath

role

Data Engineer

Source-cited RoleMath page about Data Engineer.

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Researched by RoleMath Research. Every figure on this page traces to the official source shown next to it.

What the numbers say about this work

Government occupation data for the role this maps to — Software Developers (SOC 15-1252). This is planning context for the occupation, not a salary or a job this role guarantees you.

Median pay (occupation)
$135,980 / yr · $82,460 to $214,670 (10th–90th percentile)
Projected change (2024–34)
+15.8% · ~115.2k openings/yr
Typical entry education
Bachelor's degree

BLS OEWS — occupation-level, national BLS Employment Projections 2024–34 This role uses a broad O*NET-SOC/BLS occupation mapping. Data Engineer uses the BLS Software Developers occupation as nearest labor-market context for pipeline, platform, and production data-system work. Treat salary, outlook, and task data as occupation-level evidence, not a title-specific data-engineer salary or hiring forecast.

What it pays by metro

The national median hides a wide geographic spread. Below is the occupation’s median in some of the highest-paying and largest-employment metros, adjusted for local prices — regional price-level context, not take-home pay or a salary this role guarantees you.

MetroNominal medianCost-adjusted
San Jose, CA$213,110$192,994
San Francisco, CA$186,640$161,435
Boulder, CO$164,560$156,423
Manchester, NH$162,090$153,412
Boston, MA$166,090$153,409
Bridgeport, CT$162,650$152,203

See all metros and how this is calculated → Sources: BLS OEWS (May 2025), occupation-level metro median ÷ BEA Regional Price Parities (2024, US=100).

What this work involves

The tasks the U.S. Department of Labor’s O*NET lists most central to this occupation — role-fit evidence to weigh against your background, not a measure of employer demand.

  • Analyze user needs and software requirements to determine feasibility of design within time and cost constraints.
  • Develop or direct software system testing or validation procedures, programming, or documentation.
  • Confer with systems analysts, engineers, programmers and others to design systems and to obtain information on project limitations and capabilities, performance requirements and interfaces.
  • Modify existing software to correct errors, adapt it to new hardware, or upgrade interfaces and improve performance.
  • Prepare reports or correspondence concerning project specifications, activities, or status.
  • Analyze information to determine, recommend, and plan installation of a new system or modification of an existing system.

O*NET — occupation-level

Skills that matter

The skills O*NET rates most important for this occupation. A starting map for what to build — weigh it against the specific job you’re targeting.

  • Critical Thinking
  • Active Learning
  • Reading Comprehension
  • Active Listening
  • Writing
  • Speaking
  • Monitoring
  • Mathematics

O*NET — occupation-level

Certification decision support

Certifications mapped to Data Engineer

Certifications mapped to this role from cited OEM target-role data and the RoleMath role mapping, ordered by relationship strength and then Difficulty Score. This is planning context — not a guarantee, not an employer requirement, and not a claim that any one certification is best for everyone. Your fit depends on your background; pay/outlook context is occupation-level on the role page.

Start here signalMicrosoft Certified: Azure Databricks Data Engineer Associate40/100 · Moderate

Data foundations

1 mapped

Foundational data-platform credentials before deeper engineering specialization.

CredentialDifficultyCostRelationshipWhy it appears here
Microsoft Certified: Azure Data FundamentalsMicrosoft · beginner
20/100FoundationalCost not verifiedfoundationMicrosoft Certified: Azure Data Fundamentals maps to Data Engineer as a foundation credential based on its cited track token:data-engineer signal.Official source

Microsoft Fabric, Azure, and Databricks

4 mapped

Microsoft data-engineering credentials across Fabric, Azure, and Azure Databricks.

CredentialDifficultyCostRelationshipWhy it appears here
Microsoft Certified: Azure Databricks Data Engineer AssociateMicrosoft · intermediate
40/100ModerateCost not verifiedstrong signalMicrosoft Certified: Azure Databricks Data Engineer Associate maps to Data Engineer as a strong role signal based on its cited name keyword:data engineering signal.Official source
Microsoft Certified: Fabric Analytics Engineer AssociateMicrosoft · intermediate
40/100ModerateCost not verifiedstrong signalMicrosoft Certified: Fabric Analytics Engineer Associate maps to Data Engineer as a strong role signal based on its cited name keyword:data engineering signal.Official source
Microsoft Certified: Fabric Data Engineer AssociateMicrosoft · intermediate
40/100ModerateCost not verifiedstrong signalMicrosoft Certified: Fabric Data Engineer Associate maps to Data Engineer as a strong role signal based on its cited name keyword:data engineering signal.Official source
Microsoft Certified: Azure Database Administrator AssociateMicrosoft · intermediate
40/100ModerateCost not verifiedadjacentMicrosoft Certified: Azure Database Administrator Associate maps to Data Engineer as a strong role signal based on its cited name keyword:data platform admin signal.Official source

Databricks and Spark

3 mapped

Databricks and Apache Spark credentials for lakehouse, Spark, and data-pipeline work.

CredentialDifficultyCostRelationshipWhy it appears here
Databricks Certified Associate Developer for Apache SparkDatabricks · associate
45/100Moderate$200 examstrong signalDatabricks Certified Associate Developer for Apache Spark maps to Data Engineer as a strong role signal based on its cited track token:data-engineer signal.Official source
Databricks Certified Data Engineer AssociateDatabricks · associate
45/100Moderate$200 examstrong signalDatabricks Certified Data Engineer Associate maps to Data Engineer as a strong role signal based on its cited name keyword:data engineering signal.Official source
Databricks Certified Data Engineer ProfessionalDatabricks · professional
70/100Hard$200 examadvanced adjacentDatabricks Certified Data Engineer Professional maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source

Snowflake

4 mapped

Snowflake data-engineering, Snowpark, administrator, and architect credentials.

CredentialDifficultyCostRelationshipWhy it appears here
SnowPro Specialty: SnowparkSnowflake · specialist
55/100Moderate$225 examstrong signalSnowPro Specialty: Snowpark maps to Data Engineer as a strong role signal based on its cited name keyword:data engineering signal.Official source
SnowPro Advanced: Data EngineerSnowflake · professional
80/100Expert$375 examspecializedSnowPro Advanced: Data Engineer maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source
SnowPro Advanced: AdministratorSnowflake · professional
80/100Expert$375 examadjacentSnowPro Advanced: Administrator maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source
SnowPro Advanced: ArchitectSnowflake · professional
80/100Expert$375 examadjacentSnowPro Advanced: Architect maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source

Cloud data engineering

2 mapped

AWS and Google Cloud data-engineering credentials for managed cloud data platforms.

CredentialDifficultyCostRelationshipWhy it appears here
AWS Certified Data Engineer - AssociateAmazon Web Services · Associate
60/100Hard$150 examadvanced adjacentAWS Certified Data Engineer - Associate maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Professional Data EngineerGoogle Cloud · professional
75/100Hard$200 examadvanced adjacentProfessional Data Engineer maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source

Database administration

4 mapped

Database administration credentials that are adjacent to data engineering and platform operations.

CredentialDifficultyCostRelationshipWhy it appears here
Oracle AI Database Administration Certified ProfessionalOracle · professional
60/100HardCost not verifiedadjacentOracle AI Database Administration Certified Professional maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Oracle Certified Professional, MySQL 8.0 Database AdministratorOracle · professional
60/100HardCost not verifiedadjacentOracle Certified Professional, MySQL 8.0 Database Administrator maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Professional Cloud Database EngineerGoogle Cloud · professional
80/100Expert$200 examspecializedProfessional Cloud Database Engineer maps to Data Engineer as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Oracle AI Database Administration Certified AssociateOracle · associate
40/100ModerateCost not verifiedadjacentOracle AI Database Administration Certified Associate maps to Data Engineer as a strong role signal based on its cited name keyword:data platform admin signal.Official source

Difficulty is the RoleMath Difficulty Score, not a pass rate. Certification mappings are planning context, not employer requirements, job guarantees, salary claims, or ROI claims.

Answer blocks

Common Questions

What certifications do I need to become a Data Engineer?

Certifications commonly mapped to a Data Engineer role, ordered from the lowest-difficulty starting point: Microsoft Certified: Azure Databricks Data Engineer Associate; Microsoft Certified: Fabric Analytics Engineer Associate; Microsoft Certified: Fabric Data Engineer Associate; Databricks Certified Associate Developer for Apache Spark — with advanced credentials such as AWS Certified Data Engineer - Associate, Oracle AI Database Administration Certified Professional as later steps.

Entry options, lowest difficulty first: Microsoft Certified: Azure Databricks Data Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Microsoft Certified: Fabric Analytics Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Microsoft Certified: Fabric Data Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Databricks Certified Associate Developer for Apache Spark (Databricks; Difficulty Score 45/100, Moderate; exam ~$200); Databricks Certified Data Engineer Associate (Databricks; Difficulty Score 45/100, Moderate; exam ~$200). Advanced or later-step credentials: AWS Certified Data Engineer - Associate (Amazon Web Services; Difficulty Score 60/100, Hard; exam ~$150); Oracle AI Database Administration Certified Professional (Oracle; Difficulty Score 60/100, Hard; exam fee pending vendor verification); Oracle Certified Professional, MySQL 8.0 Database Administrator (Oracle; Difficulty Score 60/100, Hard; exam fee pending vendor verification).

Citations: Source rows are visible in the page citation ledger; certification source URLs are linked in the decision table.

Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. RoleMath sells nothing.

What is the easiest certification to start a Data Engineer career?

The lowest-difficulty cited certification for starting a Data Engineer path is Microsoft Certified: Azure Databricks Data Engineer Associate (RoleMath Difficulty Score 40/100, Moderate, exam fee pending vendor verification). It is a starting signal, not a guarantee of a role.

Entry options, lowest difficulty first: Microsoft Certified: Azure Databricks Data Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Microsoft Certified: Fabric Analytics Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Microsoft Certified: Fabric Data Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification).

Citations: Source rows are visible in the page citation ledger; certification source URLs are linked in the decision table.

Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. RoleMath sells nothing.

How much do Data Engineer certifications cost and how hard are they?

Cited Data Engineer certification exam fees range roughly $150–$375, spanning from Moderate entry options to Expert credentials on the RoleMath Difficulty Score. Pay and outlook are reported at the occupation level on the Data Engineer page, never per certification.

Entry options, lowest difficulty first: Microsoft Certified: Azure Databricks Data Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Microsoft Certified: Fabric Analytics Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Microsoft Certified: Fabric Data Engineer Associate (Microsoft; Difficulty Score 40/100, Moderate; exam fee pending vendor verification); Databricks Certified Associate Developer for Apache Spark (Databricks; Difficulty Score 45/100, Moderate; exam ~$200).

Citations: Source rows are visible in the page citation ledger; certification source URLs are linked in the decision table.

Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. RoleMath sells nothing.

Data Engineer

Quick Verdict

Data Engineer maps to the BLS occupation Software Developers (SOC 15-1252), which has a national median of $135,980. Pay is occupation-level and location-driven - not caused by the job title or a certification. Below are the full cited labor-market context, the skills the role draws on, and the certification paths that map to it. This role uses a broad O*NET-SOC/BLS occupation mapping. Data Engineer uses the BLS Software Developers occupation as nearest labor-market context for pipeline, platform, and production data-system work. Treat salary, outlook, and task data as occupation-level evidence, not a title-specific data-engineer salary or hiring forecast.

Fit Signals

  • Investigative (6.05)
  • Conventional (5.62)
  • Realistic (3.61)

Skills & Tools

*Tools and technologies ONET associates with this occupation* - role-specific examples with ONET hot/in-demand flags, not employer requirements:

  • Amazon Web Services AWS software (hot technology, in demand)
  • Apache Kafka (hot technology, in demand)
  • Atlassian JIRA (hot technology, in demand)
  • C (hot technology, in demand)
  • C# (hot technology, in demand)
  • C++ (hot technology, in demand)
  • Cascading style sheets CSS (hot technology, in demand)
  • Docker (hot technology, in demand)

*Foundational ONET skills** (broadly shared across occupations, not unique to this role): Critical Thinking, Active Learning, Reading Comprehension, Active Listening, Writing, Speaking.

AI & this career

What we can — and can’t — tell you about AI and this role

Cited context only: an occupation-level outlook, descriptive usage data, an employer-language sample, and attributed research — kept separate. No RoleMath AI score, no automation timeline, no job-loss prediction. How we source this →

Occupation outlook · BLS

Where the occupation is projected to go

no BLS Employment Projections row for this role.

How AI shows up in the work

Descriptive usage, not demand or loss

For this shared SOC, the May 2026 usage sample reports 39.21% augmentation-labeled and 60.79% automation-labeled Claude conversations. Anthropic Anthropic Economic Index dataset, CC-BY.

Across all occupations the same dataset splits 51.4% augmentation / 48.6% automation (May 2026) — shown so a single role’s number is never read as an outlier.

Descriptive Claude usage data, not employment demand, not job loss, and not a personal forecast; CC-BY attribution required.

Employer language · sample

What a posting sample mentions

not yet in the posting sample.

Published research · attributed

What independent research says (not RoleMath’s claim)

  • Eloundou et al. estimate that about 80% of U.S. workers have at least 10% of their work tasks exposed to large language model capabilities (Science 2024). American Association for the Advancement of Science exposure = task overlap, not job loss.
  • Eloundou et al. estimate that about 19% of U.S. workers have at least 50% of their work tasks exposed to large language model capabilities (Science 2024). American Association for the Advancement of Science exposure = task overlap, not job loss.
  • Eloundou et al. explicitly disclaim any forecast of AI adoption or timing, describing their measure as capability overlap with tasks rather than a prediction of job loss (Science 2024). American Association for the Advancement of Science exposure = task overlap, not job loss.
  • OECD reports that high-skill occupations are the most exposed to AI on task-overlap measures (OECD Employment Outlook 2023). Organisation for Economic Co-operation and Development exposure = task overlap, not job loss.
  • OECD reports that, as of 2023, there is little empirical evidence of negative employment effects from AI (OECD Employment Outlook 2023). Organisation for Economic Co-operation and Development exposure = task overlap, not job loss.
  • OECD and the AIOE research find that AI exposure and automation risk often run in opposite directions, with the most-exposed high-skill occupations tending to be the least at risk of automation. Organisation for Economic Co-operation and Development exposure = task overlap, not job loss.
  • Felten, Raj and Seamans construct an occupation-level AI Occupational Exposure index by linking AI capabilities to O*NET occupational abilities (Strategic Management Journal). Strategic Management Journal (Wiley) exposure = task overlap, not job loss.
  • Stanford Digital Economy Lab researchers find a roughly 16% relative decline in employment for workers ages 22-25 in the most AI-exposed occupations, based on high-frequency ADP payroll data (Canaries in the Coal Mine, working paper). Stanford Digital Economy Lab correlational usage data, not proof.
  • The ILO notes that AI-exposure indicators measure potential task overlap and cannot by themselves establish job loss (Workers' exposure to AI). International Labour Organization exposure = task overlap, not job loss.
  • The Anthropic Economic Index reports no measured systematic rise in unemployment attributable to AI in its usage data. Anthropic correlational usage data, not proof.

Tier A research stays attributed and separate from BLS outlook and employer-language samples.

Every page here connects to the same cited data spine — these are the closest surfaces to what you just read.

Roles & paths this connects to

role role cost and timeWhat it costs and how long to become a Data Engineerrole role learning roadmapLearning roadmap: how to become a Data Engineerrole starter planYour starter plan: becoming a Data Engineer

Zoom out

relevant learning programClaude 101relevant learning programAI Fluency: Framework & Foundationsrelevant learning programAnthropic Academy

Every figure on this page, sourced

The claims above trace to these records — the source, and when it was last checked. If a figure has no row here, we did not publish it.

IDSupportsSourceChecked
SCHEMA-CIT-1Schema citationData Engineer BLS OEWS wage sourceLogged in source packet
SCHEMA-CIT-2Schema citationData Engineer BLS Employment Projections sourceLogged in source packet
SCHEMA-CIT-3Schema citationData Engineer O*NET sourceLogged in source packet

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