Responsibilities

• Collaborate with business partners and stakeholders to understand data requirements.
• Work with engineering, product teams, and customers to collect and integrate data.
• Design, develop, and implement high-performance data models and pipelines for Data Lake and Data Warehouse.
• Develop and enforce data quality checks, conduct QA, and set up monitoring routines.
• Enhance the reliability and scalability of ETL processes.
• Manage a portfolio of data products that ensure high-quality and trustworthy data.
• Onboard and support new engineers joining the team.

Requirements

• 5+ years of professional experience in data engineering, business intelligence, or a related role.
• 3+ years of experience with ETL orchestration and workflow management tools (like Databricks, Airflow, Flink, Oozie, Azkaban) using AWS/GCP.
• Proficiency in Python, dbt, SQL, and distributed computing with strong database fundamentals,
• 3+ years of experience with distributed data ecosystems (like Spark, Hive, Druid, Presto) and streaming technologies (like Kafka, Flink).
• Experience with Snowflake, Redshift, PostgreSQL, or other DBMS platforms.
• Familiarity with reporting tools like Tableau, Superset, or Looker.
• Excellent communication skills; experience working with technical and non-technical teams.
• Self-starter with strong organizational skills, comfortable in a fast-paced environment.
• Strategic thinker with the ability to analyze and interpret market and consumer data.

What We Offer

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• Opportunities for growth and development
• A collaborative and innovative work culture