N-iX

Senior/Lead Data Engineer

7000 - 8000 USD/ mies./ mies.B2BB2B (netto)

SeniorZdalnie·KrakówFull-time·B2B

#447103·Dodano miesiąc temu·3

Źródło: justjoin.it

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Tech Stack / Keywords

Data EngineeringSQL Airflow AWSAWS Athena, AWS Data Lake

Podsumowanie oferty

The Senior/Lead Data Engineer will support the client team by maintaining and extending data pipelines and data models to power analytics and reporting. The role involves working closely with data analysts and business stakeholders to translate business requirements into robust data solutions, using technologies like SQL, Airflow, Athena, and AWS Data Lake. The engineer will ensure data quality, troubleshoot issues, and use AI-assisted engineering tools effectively.

Wymagania

Hands-on data engineering experience building and operating production data pipelines, ideally within analytics-driven environments.
Strong SQL skills.
Experience with data modeling for analytics, including fact and dimension tables.
Experience with workflow orchestration, preferably Airflow.
Experience working with AWS-based data environments, particularly Athena and AWS Data Lake.
Experience with data validation, testing, and troubleshooting.
Strong sense of ownership and engineering judgment: comfortable working with incomplete requirements, proactively seeking context, challenging assumptions when appropriate, and looking for practical solutions rather than stopping at the first blocker.
Excellent verbal and written English skills, with clear communication across data analysts, engineers, and business stakeholders.

Nice to have:

Experience with data mesh architectures or working in a data mesh environment.
Experience with marketplace, web/app, or digital analytics data.
Experience with DBT and/or Snowflake.
Familiarity with AI-assisted engineering tools such as Codex.

Obowiązki

Maintain, troubleshoot, and improve existing data pipelines, and build new pipelines and datasets based on analytics and business requirements.
Design and maintain analytical data models, including fact and dimension models.
Ingest and integrate data from different source systems into the AWS Data Lake.
Build, deploy, validate, monitor, and, when necessary, backfill data pipelines.
Partner with data analysts to understand their requirements and provide reliable, easy-to-use datasets.
Clarify requirements with business stakeholders rather than implementing ambiguous requests as-is.
Ensure data quality through appropriate validation and testing, investigating data and pipeline issues and taking ownership of finding pragmatic solutions end to end.
Use AI-assisted development tooling effectively while critically reviewing and validating generated solutions.

Inne informacje

N-iX Krakow, Zabłocie Business Park business centre, Zabłocie 43A, 30-70

N-iX

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