Mid-Level Data Engineer — ETL Pipelines & Data Lakes (Remote)

externaljobboards; Polska; Hybrid; PLN 150,000 - 230,000; Full time

Benefits offered by this job

International projects

In-office, hybrid, or remote flex

Medical healthcare

Recognition program

Ongoing learning & reimbursement

Well-being program

Team events & local benefits

Sports compensation

Referral bonuses

Top-tier equipment provision

Job summary

Exadel is seeking a data engineering professional to design, build, and optimize ETL/ELT pipelines, transforming both customer and internal data into actionable datasets. You will collaborate with Markets and Product teams to create dashboards that guide strategy and serve client needs.

You will also build and maintain data lakes and feature stores used by the ML Engineering team to develop ML solutions for subrogation, leveraging Spark, AWS data services, and modern data architectures.

Qualifications

• Proficient in Python and SQL for data processing and pipeline development.
• Experience with distributed processing technologies, especially Spark.
• Hands-on experience with AWS data services (Glue, S3, Step Functions, Athena, EMR, DynamoDB, SQS).
• Familiar with data lake architectures (bronze/silver/gold) and schema management.
• Ability to debug data quality issues across distributed systems and implement data quality frameworks.

Responsibilities

• Design, build, and optimize ETL/ELT pipelines that transform customer and internal data into actionable datasets
• Partner with Markets and Product teams to develop reporting tools and dashboards that guide business strategy and serve customer needs
• Build and maintain data lakes and feature stores used by ML Engineering to develop ML solutions for subrogation

Skills

Python

SQL

Data Modeling

Data Quality

Debugging

Tools

Spark

AWS Glue

Amazon S3

Step Functions

Athena

EMR

DynamoDB

SQS

Kafka

MongoDB

Terraform

CloudFormation

Job description

Exadel is seeking a data engineering professional to design, build, and optimize ETL/ELT pipelines, transforming both customer and internal data into actionable datasets. You will collaborate with Markets and Product teams to create dashboards that guide strategy and serve client needs.

You will also build and maintain data lakes and feature stores used by the ML Engineering team to develop ML solutions for subrogation, leveraging Spark, AWS data services, and modern data architectures.