Exadel
Vehicle lifecycle solutions
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Exadel. Skills: ETL/ELT pipelines, Data lakes, Feature stores, ML solutions. Design ETL/ELT pipelines. Build ETL/ELT pipelines”
Industry & Context.
Analytical challenges; Debug data quality
What They're Looking For.
Must Have
Proficiency in Python, Proficiency in SQL, Experienced in Spark, Deep experience AWS data services, Experience data streaming technologies, Experienced in data modeling, Familiarity with MongoDB, Comfort with IaC, Ability to debug data quality issues, Experience implementing data quality frameworks
Nice to Have
Data modeling in finance, Data modeling in insurance, English Upper-Intermediate
What You'll Do.
Design ETL/ELT pipelines
Build ETL/ELT pipelines
Optimize ETL/ELT pipelines
Transform customer data
Transform internal data
Develop reporting tools
Maintain feature stores
How You'll Work.
Team & Collaboration
Partner with Markets; Partner with Product; ML Engineering team
Full Job Description
Join Exadel as a Senior Data Engineer and bring logic to life. Solve analytical challenges and build solutions that matter—with a sharp, collaborative team. Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers. What You'll Do 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 team to develop ML solutions for subrogation What You Bring Strong proficiency in Python and SQL Experienced in Spark or similar distributed processing technologies Deep experience with AWS data services (Glue, S3, Step Functions, Athena, EMR, DynamoDB, SQS) Experience working with data streaming technologies (Kafka, Spark Streaming, etc.) Experienced in data modeling (preferably in finance or insurance) Familiarity with MongoDB and document-oriented data sources Experience with data lake patterns: medallion archite
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