Resume Example & Template

Data Engineer Resume Example

What the role is, a real Data Engineer resume example, and exactly what recruiters look for — then build your own in minutes.

Build your Data Engineer resume

What is a Data Engineer?

A Data Engineer builds and maintains the pipelines and platforms that move, store, and shape an organisation’s data. They turn raw, messy sources into clean, reliable, well-modelled datasets that analysts, data scientists, and ML systems can trust.

The work spans ingestion, ETL/ELT, data modelling, orchestration, and the reliability around it — testing, lineage, and monitoring. Modern Data Engineers work across cloud warehouses and lakehouses (Snowflake, BigQuery, Databricks) and orchestration tools (Airflow, dbt) to deliver data as a dependable product.

As every team becomes data- and AI-driven, the Data Engineer is one of the most consistently in-demand roles — the foundation that analytics, BI, and machine learning all sit on.

Key skills for a Data Engineer resume

  • Advanced SQL & data modelling (star/snowflake, dimensional)
  • Python for data pipelines
  • ETL/ELT & orchestration (dbt, Airflow, Dagster)
  • Cloud warehouses & lakehouses (Snowflake, BigQuery, Databricks, Redshift)
  • Batch & streaming (Spark, Kafka, Flink)
  • Cloud infrastructure (AWS, Azure, GCP)
  • Data quality, testing & lineage
  • Governance, security & cost optimisation

Data Engineer resume example

Daniel Okoye

Data Engineer

Amsterdam, Netherlands

Summary

Data Engineer with 7+ years building cloud data platforms and ELT pipelines that serve analytics and ML at scale. Expert in SQL, dbt, and Airflow on Snowflake and BigQuery, with a track record of cutting cost and runtime while raising data reliability.

Experience

Senior Data Engineer · Adyen

Feb 2021 – Present

  • Designed and own the ELT platform (Snowflake + dbt + Airflow) serving 300+ analysts and 40+ data products across the company.
  • Cut core pipeline runtime 60% and warehouse spend 30% through incremental models, clustering, and warehouse right-sizing.
  • Built a data-quality framework with dbt tests, contracts, and lineage that eliminated recurring reporting incidents.
  • Introduced streaming ingestion with Kafka for near-real-time payment analytics.

Data Engineer · Booking.com

Aug 2018 – Jan 2021

  • Built batch pipelines on GCP (BigQuery, Dataflow) processing 5TB+/day for marketing and product analytics.
  • Modelled dimensional warehouses and optimised SQL, improving dashboard query performance 4x.

Education

MSc Software Engineering

University of Amsterdam · 2016 – 2018

BSc Computer Science

University of Lagos · 2011 – 2015

Certifications

  • SnowPro Core — Snowflake
  • Google Cloud Professional Data Engineer
  • dbt Analytics Engineering Certification

Skills

Languages: SQL · Python · Bash · Scala

Warehouse & Transform: Snowflake · BigQuery · dbt · Databricks

Orchestration & Streaming: Airflow · Dagster · Kafka · Spark

Cloud: AWS · GCP · Azure · Terraform

Use this as your starting point

How to write a Data Engineer resume that stands out

  • Quantify scale — rows, TB processed, pipelines owned, and users/teams served. Data engineering is a scale game and reviewers look for it.
  • Show impact on reliability and cost (e.g. “cut pipeline runtime 60%”, “reduced warehouse spend 30%”, “eliminated data incidents”).
  • Name the exact stack — warehouse, orchestration, transformation, and streaming tools. ATS and technical screeners search for specific tech.
  • Highlight data quality and governance work (testing, lineage, contracts) — it separates a senior data engineer from a scripting one.
  • Frame datasets as products with SLAs and consumers, not one-off scripts.

Data Engineer resume — FAQ

What does a Data Engineer do?

A Data Engineer designs, builds, and maintains the pipelines and platforms that ingest, transform, model, and store data. They deliver clean, reliable datasets — with testing, orchestration, and monitoring — so analysts, data scientists, and ML systems can use data with confidence.

What skills should a Data Engineer put on a resume?

Advanced SQL and data modelling, Python, ETL/ELT and orchestration (dbt, Airflow), a cloud warehouse or lakehouse (Snowflake, BigQuery, Databricks), batch and streaming (Spark, Kafka), cloud infrastructure, and data quality/governance. Cost optimisation and lineage are strong differentiators.

How is a Data Engineer different from a data analyst?

A data analyst uses data to answer business questions and build reports. A Data Engineer builds the infrastructure and pipelines that make trustworthy data available in the first place — focusing on scalability, reliability, and modelling rather than analysis.

What should a Data Engineer resume include?

Lead with a summary that frames you as a builder of reliable data platforms. Show pipelines and models you own with scale and impact (runtime, cost, reliability), the exact stack (warehouse, dbt, Airflow, Spark), and data quality/governance work. Keep it ATS-safe with clean structure and real text.

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