Senior Data Engineer

Role Summary:

We are seeking an experienced Senior Data Engineer who thrives on defining solutions and shaping data infrastructure in a dynamic environment. You will take a significant role in enhancing our data platform (Postgres, BigQuery, Python/Prefect, Dataform) and establishing robust data engineering practices, directly enabling the delivery of business value through reliable, high-quality data.

Responsibilities:

• Architect and implement core data infrastructure: You will design, build, and optimize data ingestion pipelines (Python/Prefect), data warehouse models (BigQuery/Postgres with Dataform), and foundational datasets. Your work will directly enable the availability of high-quality data for analytics and operational use, forming the backbone for business value generation.
• Drive data quality and platform reliability: You will establish and enhance data quality frameworks, implement monitoring and alerting for our data systems, and ensure the overall stability and performance of the data platform. This focus ensures that the data delivered is trustworthy and readily accessible, which is critical for business decision-making.
• Lead the evolution of data engineering practices and capabilities: You will actively contribute to defining, documenting, and improving our data engineering processes, development standards, and infrastructure components. This involves identifying areas for increased efficiency, scalability, and cost-effectiveness, enabling the team to deliver more value over time.
• Collaborate to translate business needs into effective data solutions: You will work closely with analytics engineers, data analysts, and business stakeholders to understand their requirements and challenges, translating these into practical and impactful data solutions that support strategic objectives.

Requirements

• Experience:
  •  5+ years of hands-on experience in data engineering or a similar role, with substantial experience in environments where you played a key role in building, defining, or significantly improving data platforms and processes.
• Initiative & Problem-Solving:
  • A proactive problem-solver, capable of independently identifying opportunities for improvement, defining solutions, and leading their execution in environments undergoing active development.
• Technical Expertise:
  • Strong proficiency in Python for data processing and pipeline development.
  • Proven experience in data modeling (conceptual, logical, physical), ETL/ELT design, and building scalable data warehousing solutions (e.g., BigQuery, Postgres).
  • Hands-on experience with orchestration tools (e.g., Prefect, Airflow, or similar).
  • In-depth knowledge of cloud-based data warehouses, specifically Google BigQuery; experience with Postgres is also required.
  • Practical experience in designing and implementing data quality frameworks, monitoring systems, and alerting mechanisms.
  • Familiarity with data transformation tools (e.g., Google Dataform, dbt).
    

Preferred Qualifications:

• Experience working directly with business users to gather requirements and deliver data solutions.
• Understanding of data governance principles and their practical application.
• Experience with BI tools and an understanding of how data models support self-service analytics.
• Previous contributions to establishing data engineering best practices, coding standards, or CI/CD processes for data pipelines.

Benefits

• Opportunity to work on high-impact projects in a rapidly evolving AI landscape.
• A supportive environment that values continuous learning, innovation, and professional growth.
• Collaboration with a diverse team of experts in data science, machine learning, and engineering.
• Competitive compensation package and benefits.