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Data Engineer II

Data Engineer II

RELX
2-5 Years
Not Disclosed
  • Posted 7 hours ago
  • Be among the first 10 applicants

Job Description

Accountabilities

  • Develop, test, and maintain ETL/ELT pipelines that ingest structured and semi-structured data from third-party sources, including GA4, paid media, social media, and other marketing platforms.
  • Build and support API and batch-ingestion workflows, including pagination, rate-limit handling, retries, and incremental loads.
  • Integrate web traffic, campaign, engagement, and related business data into the AWS data lake.
  • Transform source data into consistent, reusable datasets using established standards for data types, normalization, deduplication, and validation.
  • Monitor scheduled pipelines and troubleshoot data-quality, performance, schema, and processing issues.
  • Implement data-quality checks and communicate failures, risks, and blockers to the appropriate team members.
  • Work with AWS data services such as S3, Glue, Athena, and CloudWatch, or equivalent cloud technologies.
  • Use Git-based development practices, including branches, pull requests, peer reviews, and controlled deployments.
  • Perform unit testing and source-to-target validation for pipeline changes.
  • Maintain technical documentation for data sources, mappings, transformations, business rules, and operational procedures.
  • Collaborate with Sr. Engineers, reporting analysts, and business stakeholders to translate requirements into technical tasks.
  • Implement established data-governance, privacy, consent, access, and retention requirements.
  • Participate in Agile planning, estimation, demonstrations, and retrospectives.
  • Responsibly use approved enterprise AI tools while validating generated code and protecting company and customer data.

Qualifications

  • Typically 2–5 years of experience in data engineering, database development, software engineering, analytics engineering, or a related role.
  • Working proficiency in SQL and Python.
  • Experience developing or supporting ETL/ELT pipelines.
  • Hands-on experience with AWS or another cloud-based data platform.
  • Experience working with relational databases such as PostgreSQL, Microsoft SQL Server, or Oracle.
  • Experience processing structured and semi-structured formats such as JSON, CSV, and Parquet.
  • Familiarity with API ingestion, authentication, pagination, batch processing, incremental loading, and data validation.
  • Familiarity with Git, pull requests, code reviews, testing, and deployment workflows.
  • Ability to investigate data issues and communicate progress, risks, and blockers clearly.
  • Ability to collaborate with technical and business stakeholders in a global environment.
  • Strong problem-solving, organizational, documentation, and communication skills.
  • Ability to work 8 hours of overlap with [Eastern/Central] US business hours
  • Ability to quickly learn and apply enterprise AI tools and technologies to support technical workflows and business objectives.

Preferred Qualifications

  • Experience with GA4 data models or APIs.
  • Familiarity with marketing attribution, campaign tracking, and UTM structures.
  • Experience working with paid-media or social-media APIs.
  • Familiarity with AWS S3, Glue, Athena, and CloudWatch.
  • Familiarity with Databricks, PySpark, Airflow, or similar data-processing and orchestration technologies.
  • Experience working in an Agile environment.

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