Data engineer

📐 About this role

We’re looking for a Data Engineer to help design, build, and scale the data infrastructure that powers our analytics, reporting, and product insights. As part of a small but high-impact Data team, you’ll define the architectural foundation and tooling for our end-to-end data ecosystem.

You’ll work closely with engineering, product, and business stakeholders to build robust pipelines, scalable data models, and reliable workflows that enable data-driven decisions across the company.

If you are passionate about data infrastructure, and solving complex data problems, we want to hear from you!

🖥️ Tech stack

Core tools: Snowflake, BigQuery, dbt, Fivetran, Hightouch, Segment

Periphery tools: AWS DMS, Google Datastream, Terraform, GithHub Actions

🦸🏻‍♀️ What you’ll do

• Data infrastructure:

  • Design efficient and reusable data models optimized for analytical and operational workloads.

  • Design and maintain scalable, fault-tolerant data pipelines and ingestion frameworks across multiple data sources.

  • Architect and optimize our data warehouse (Snowflake/BigQuery) to ensure performance, cost efficiency, and security.

  • Define and implement data governance frameworks — schema management, lineage tracking, and access control.

• Data orchestration:

  • Build and manage robust ETL workflows using dbt and orchestration tools (e.g., Airflow, Prefect).

  • Implement monitoring, alerting, and logging to ensure pipeline observability and reliability.

  • Lead automation initiatives to reduce manual operations and improve data workflow efficiency.

• Data quality:

  • Develop comprehensive data validation, testing, and anomaly detection systems.

  • Establish SLAs for key data assets and proactively address pipeline or data quality issues.

  • Implement versioning, modularity, and performance best practices within dbt and SQL.

• Collaboration & leadership:

  • Partner with product and engineering teams to deliver data solutions that align with downstream use cases.

  • Establish data engineering best practices and serve as a subject matter expert on our data pipelines, models and systems.

⭐️ What we’re looking for

• 5+ years of hands-on experience in a data engineering role, ideally in a SaaS environment.

• Expert-level proficiency in SQL, dbt, and Python.

• Strong experience with data pipeline orchestration (Airflow, Prefect, Dagster, etc.) and CI/CD for data workflows.

• Deep understanding of cloud-based data architectures (AWS, GCP) — including networking, IAM, and security best practices.

• Experience with event-driven systems (Kafka, Pub/Sub, Kinesis) and real-time data streaming is a plus.

• Strong grasp of data modeling principles, warehouse optimization, and cost management.

• Passionate about data reliability, testing, and monitoring — you treat pipelines like production software.

• Thrive in ambiguous, fast-moving environments and enjoy building systems from the ground up.

🧠 Who you are

• Intellectually curious and driven by building scalable systems that last.

• Pragmatic problem solver who values simplicity and clarity in design.

• Excellent communicator who can bridge technical and business perspectives.

• Humble, resilient, and motivated by impact over recognition.

• Embody our values: Connect, Challenge, Own.

🍩 Benefits & perks (US Full-time employees)

• Generous PTO, plus company holidays

• Medical, dental, and vision coverage for you and your family

• Paid parental leave for all parents (12 weeks)

• Fertility and family planning support

• Early-detection cancer testing through Galleri

• Flexible spending account and dependent FSA options

• Health savings account for eligible plans with company contribution

• Annual work-life stipends for:

  • Home office setup, cell phone, internet

  • Wellness stipend for gym, massage/chiropractor, personal training, etc.

  • Learning and development stipend

• Company-wide off-sites and team off-sites

• Competitive compensation, company stock options and 401k

WRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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