Senior Data Engineer
Indexed description
Responsibilities
Architecture & Scalability: Design, build, and optimize scalable batch and real-time streaming data pipelines (ETL/ELT) to process millions of financial events.
- Financial Data Infrastructure: Build secure data lake houses and warehouses for transactions, ledger entries, risk metrics, and customer interaction data.
Data Quality & Observability: Build automated testing, reconciliation frameworks, and real-time monitoring to guarantee zero-data-loss and auditability.
Cross-Functional Ownership: Partner with product managers, quantitative risk analysts, machine learning engineers, and finance teams to power real-time fraud engines, credit scoring models, and executive dashboards.
Qualifications & Requirements
3 years in software or data engineering with a track record of handling high-volume production data.
Strong Fintech / High-Growth DNA: You thrive in fast-moving, high-autonomy environments where you ship clean, production-grade code.
Proven Stack Mastery:
- Languages: Advanced Python and/or Scala, plus expert SQL.
- Streaming & Processing: Hands-on experience with Kafka, Spark, or Flink.
- Warehousing & Orchestration: Snowflake, Databricks, or BigQuery + Airflow or Dagster.
- Infrastructure as Code: Docker, Kubernetes, Terraform, AWS or GCP.
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