Role Summary:

We are looking for a hands-on Data Engineer / Analyst to design and maintain high-throughput, high-trust data pipelines—from 35 MB CSVs today to 100+ MB multi-source feeds. You will enable critical forecasting and ML workflows by transforming raw data into well-modeled, auditable datasets and feature stores.

Key Responsibilities:

• Design and implement ELT pipelines from staging to star-schema using TypeScript + Drizzle ORM in a cron-based (Airflow-lite) orchestration.
• Embed robust data-quality gates: null checks, schema-drift detection, re-weighting logic for post-COVID data, and outlier flags.
• Build and maintain feature stores for calendar/holiday events, price/promo tracking, payment methods, and customer segments.
• Optimize ingestion and transformation performance to meet <20-minute ingest SLAs, using chunked uploads, intelligent partitioning, and materialized views.
• Maintain accurate data dictionaries, ERDs, and lineage diagrams to support auditability and technical documentation.

Required Technical Skills:

• Strong command of Advanced SQL and PostgreSQL tuning.
• Proficiency in TypeScript and/or Python for scripting and data processing.
• Experience building transformations using dbt-style paradigms (modular, versioned, testable).
• Basic experience with Git, Docker, and CI/CD pipelines.

Nice-to-Have Skills:

• Familiarity with Airflow or Airbyte for workflow/data integration orchestration.
• Experience working with Parquet, Apache Arrow, or other columnar formats.
• Ability to do quick BI-level validations and support analysts with ad-hoc insights.

Soft Skills:

• Attention to detail and a strong bias for data accuracy and reproducibility.
• Proactive communicator – reports anomalies and issues early and clearly.
• Collaborative mindset – works comfortably across ML, QA, and Documentation teams.

Why Join Us?

• Work with a forward-thinking team solving real-world forecasting and data modeling challenges.
• Opportunities to shape architectural decisions and influence data governance practices.
• Flexible work arrangements and a culture of ownership and transparency.