Data Engineer Resume: Free Template & Example 2026

A technically rigorous data engineer resume highlighting large-scale pipeline architecture, cloud infrastructure, and real-time data processing expertise.

Contact

lena.kowalski@email.com

+48 512 555 738

Warsaw, Poland

linkedin.com/in/lenakowalski

lenakowalski.dev

Skills

Apache Spark / PySparkKafka / FlinkSQL / dbt / SnowflakeAWS / GCP / TerraformPython / Scala

Languages

Polish

Native

English

C2

German

A2

Interests

Open SourceBoulderingBoard Games

Lena Kowalski

Senior Data Engineer

Profile

Senior data engineer with 6+ years designing and maintaining petabyte-scale data platforms. Skilled in Apache Spark, Kafka, and cloud-native architectures on AWS and GCP.

Experience

Senior Data Engineer2022 - Present | Warsaw, Poland

Allegro

>Architected real-time event streaming platform processing 2B+ events/day on Apache Kafka and Flink

>Reduced data pipeline costs by 45% through partition pruning and Spark query optimisation

>Led migration of 60+ legacy ETL jobs to Airflow-orchestrated dbt pipelines

Data Engineer2019 - 2022 | London, UK

Revolut

>Built customer risk-scoring pipeline serving 15M+ users with sub-second latency

>Designed Snowflake data warehouse schema supporting 200+ downstream dashboards

>Implemented data quality framework catching 98% of anomalies before reaching production

Projects

OpenLineage Contributor2023

Core contributor to OpenLineage open-source project — authored Spark integration used by 400+ companies

Education

MSc Computer Science2019

University of Warsaw

Certifications

AWS Certified Data Analytics – Specialty2023

Amazon Web Services

Create your Data Engineer Resume

Key Skills for a Data Engineer Resume

A strong data engineer resume showcases expertise in building and maintaining data infrastructure. Include programming languages (Python, Scala, Java, SQL), ETL/ELT tools (Apache Spark, Airflow, dbt), and cloud platforms (AWS, GCP, Azure). Highlight experience with data warehousing (Snowflake, BigQuery, Redshift), streaming systems (Kafka, Kinesis), and orchestration frameworks. Knowledge of data modeling, schema design, and data quality practices is essential for standing out.

Tips for Your Data Engineer Resume

Quantify pipeline performance: data volumes processed, latency reductions, and cost savings achieved. Describe the architectures you have built, not just the tools you have used. Include migration projects and their business impact. Show experience with both batch and real-time processing. Mention data governance and security practices. Keep technical jargon precise and relevant to the target role.

Sections to Highlight

Your Experience section should detail data platforms built, pipeline complexity, and business outcomes enabled. The Skills section must list languages, frameworks, cloud services, and databases with specificity. Education in computer science, engineering, or mathematics provides foundation. Certifications like AWS Data Engineer or Google Professional Data Engineer add significant credibility. Projects demonstrating end-to-end pipeline design strengthen your application.