Senior Data Engineer ID71671

AgileEngine

$110K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years of experience as a Data Engineer
  • Proficient in core Python programming with a focus on modular, maintainable code
  • Advanced SQL expertise, including query optimization and data modeling
  • Hands-on experience with Snowflake for data warehousing
  • Production-level experience in workflow orchestration frameworks like Airflow, Prefect, or Dagster
  • Experience integrating REST APIs and managing streaming and batch data ingestion
  • Familiarity with automated data quality checks and lineage tracking mechanisms
  • Proficient in Git, Docker, and basic Infrastructure-as-Code practices

Responsibilities

  • Design, build, and maintain scalable ETL/ELT workflows for diverse data sources
  • Create efficient and optimized data models within Snowflake
  • Integrate third-party REST APIs and event-driven data sources
  • Maintain and develop orchestration pipelines using Airflow, Prefect, or Dagster
  • Implement automated tests and validation frameworks for data integrity
  • Drive best practices in CI/CD and maintain code standards
  • Ensure high-quality code through design patterns and documentation

Benefits

  • Access to mentorship, TechTalks, and a dedicated learning budget
  • Regular performance and compensation reviews to recognize skills and impact
  • 100% remote work with flexible hours
  • Engagement in meaningful projects using modern technologies
  • A collaborative culture that values contributions without micromanagement
  • Supportive well-being programs tailored to employee location
Full Job Description
Job Description

ABOUT THE ROLE

We are looking for a Senior Data Engineer to architect, build, and scale a modern data platform - designing production-grade ETL/ELT pipelines, optimizing Snowflake data warehouse schemas, and establishing robust DataOps practices. You will orchestrate workflows using Airflow, Prefect, or Dagster, implement data quality and lineage frameworks, integrate third-party REST APIs and event-driven sources, and apply software engineering standards including CI/CD, Docker, and automated testing to data repositories. The role prioritizes clean, well-tested Python code and a deep commitment to data reliability and accessibility.

WHAT YOU WILL DO

- Data Pipeline Development: Design, build, and maintain reliable, scalable ETL/ELT workflows that process batch and streaming data from diverse sources.

- Data Warehousing & Modeling: Design efficient, production-ready schemas (normalized and denormalized) in Snowflake to optimize query performance and enable enterprise analytics.

- API & Event Integration: Connect and ingest data from third-party REST APIs, event-driven streams, and batch sources into core data storage platforms.

- Orchestration: Maintain and expand workflow orchestration pipelines using modern tools (Airflow, Prefect, or Dagster).

- Data Quality & Observability: Implement automated testing, validation, lineage tracking, and proactive alerting frameworks to guarantee data accuracy and system uptime.

- DataOps & Engineering Standards: Drive CI/CD best practices, maintain code bases using Git and Docker, and adopt basic Infrastructure-as-Code (IaC) patterns.

- Code Excellence: Apply modern software engineering standards-including design patterns, automated unit/integration testing, and clear documentation-to data repositories.

MUST HAVES

- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;

- 4+ years of experience as a Data Engineer.

- Core Python Fundamentals: Demonstrable expertise writing modular, maintainable, and well-tested Python code (OOP/functional patterns, package management, standard testing frameworks).

- Advanced SQL & Modeling: Deep knowledge of complex SQL queries, query optimization, database design principles, and normalization/denormalization patterns.

- Data Warehousing: Solid, hands-on experience building, managing, and optimizing data architectures within Snowflake.

- Workflow Orchestration: Production experience using workflow orchestration engines like Apache Airflow, Prefect, or Dagster.

- Integrations & Ingestion: Hands-on experience working with REST APIs, event-driven architectures, and both batch and streaming pipelines.

- Data Quality & Lineage: Experience building automated data quality checks, data lineage, and alerting mechanisms (e.g., using tools like dbt test, Great Expectations, or similar).

- DevOps / DataOps Practices: Strong skills in version control (Git), containerization (Docker), CI/CD automation, and familiarity with Infrastructure-as-Code basics.

- Upper-intermediate English level.

NICE TO HAVES

- Experience with dbt (data build tool) for data transformations.

- Familiarity with major cloud providers (AWS, GCP, or Azure).

- Exposure to message streaming tech like Apache Kafka or AWS Kinesis.

PERKS AND BENEFITS

- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget

- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews

- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm

- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands

- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized

- Well-being & support: access local well-being programs and people-focused support tailored to your location

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