Staff Data Engineer

Roles and Responsibilities

• • Design and evolve canonical and medallion-layer data models (bronze/silver/gold) that enable scalable, governed data across the organization.
  • Build and optimize ETL/ELT pipelines using Apache Airflow, Spark, Trino and cloud-native tools.
  • Develop high-performance data marts and semantic layers that serve analytics and data science needs.
  • Architect streaming and analytical systems using Kafka and ClickHouse for real-time and batch insights.
  • Define and enforce standards for data modeling, documentation, quality, and lineage across all domains.
  • Partner with Analytics, AI/ML, and Infrastructure teams to translate business logic into reusable, trusted data assets.
  • Mentor engineers, lead design reviews, and drive continuous improvement in scalability and data reliability.
  • Champion a culture of data clarity, consistency, and craftsmanship, aligning systems to business goals.

Technical Qualification -

• • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
  • 10+ years of experience in Data Engineering, including 2+ years in a senior or staff-level technical role.
  • Expertise in SQL, data modeling, and data mart design.
  • Deep hands-on experience with Apache Airflow, dbt, Spark, Kafka, and ClickHouse.
  • Proven experience designing medallion data architectures and scalable data lakehouse solutions.
  • Proficiency in Python or Scala, and familiarity with AWS, GCP, or Azure data ecosystems.
  • Strong understanding of data governance, lineage, and quality frameworks.
  • Demonstrated ability to mentor engineers and influence architectural strategy across teams.

• • Experience with real-time or streaming data (Kafka, Kinesis, or Pub/Sub).
  • Knowledge of data observability and catalog tools (DataHub, Amundsen, Monte Carlo, Great Expectations, or Soda).
  • Experience in eCommerce, retail analytics, or digital marketplaces.
  • Exposure to governed data contracts and semantic layer frameworks.
  • Proven track record of leading data architecture initiatives or cross-functional platform modernization.
  • Contributions to open-source data tools or engagement in data community initiatives