Data Engineer

About the role

This is not a traditional backend software engineering or pure data analytics position. The ideal candidate has directly built production-grade data pipelines and is highly proficient in SQL, Python, dbt, and modern ELT infrastructure.

Responsibilities

• Build and maintain reliable pipelines that ingest data from MongoDB, Airtable, PostHog, production databases, SaaS platforms, and other sources.
• Design dbt models that transform fragmented raw data into standardized, production-ready schemas.
• Develop scalable and fault-tolerant ELT/ETL workflows using Fivetran, dbt, SQL, and Python.
• Own data reliability across the full lifecycle from ingestion and transformation to downstream consumption.
• Establish automated data-quality checks, monitoring, alerting, and documentation.
• Diagnose pipeline failures, data discrepancies, schema changes, and performance bottlenecks.
• Improve pipeline scalability, processing speed, cost efficiency, and maintainability.
• Partner with Data Science, Engineering, Product, and Operations teams to understand requirements and deliver usable datasets.
• Support analytics, reporting, experimentation, and machine-learning workflows.
• Promote strong standards for data governance, lineage, schema design, and access management.

Requirements

• Professional experience in data engineering or software engineering with significant ownership of data infrastructure.
• Advanced SQL skills, including complex transformations, joins, window functions, query optimization, and data validation.
• Strong Python experience for pipeline development, automation, integrations, and data processing.
• Hands-on experience building and maintaining production-grade ETL or ELT pipelines.
• Practical experience with dbt and a cloud data warehouse such as Snowflake, BigQuery, Redshift, or Databricks.
• Experience integrating data from multiple source types, including production databases, analytics platforms, APIs, and SaaS tools.
• Strong understanding of dimensional modeling, schema design, transformation patterns, and data warehousing.
• Experience implementing monitoring, testing, and data-quality controls.
• Ability to investigate ambiguous data problems and take ownership through resolution.
• Strong communication skills and comfort working across engineering and nontechnical teams.

Preferred Qualifications

• Experience with Fivetran or a comparable managed ingestion platform.
• Experience working with MongoDB, Airtable, PostHog, or similar tools.
• Familiarity with workflow orchestration technologies such as Airflow, Dagster, or Prefect.
• Experience supporting machine-learning pipelines, experimentation systems, or analytics platforms.
• Familiarity with data lineage, governance, privacy, and access-control practices.
• Experience working in a fast-paced startup or high-growth technology company.

Note: Client is looking for US Citizen or Green Card Holder. Must be from a big tech company, small startup, or a good university.