Senior Data Engineer, Pontera

• We are seeking a highly skilled Senior Data Engineer to join our growing team
• Experience: 5+ years in a data-engineering role in the tech industry, with a proven track record of scaling data platforms in cloud environments (AWS, GCP, or Azure)
• Technical Skills: Expert SQL and Python; hands-on with Snowflake (or Redshift/BigQuery) and DBT. An advantage- Orchestration tools such as Airflow; familiarity with CI/CD, Docker, and infrastructure-as-code (e.g., Terraform), Familiarity with BI tools (Looker, Tableau) from a data-engineering perspective
• Data Architecture: Deep understanding of dimensional modeling, CDC, and ELT best practices; experience integrating third-party APIs and event streams
• Quality & Reliability: Demonstrated success implementing data-quality frameworks and building highly reliable pipelines
• Business Acumen: Experience in FinTech, SaaS, or high-growth startup environments is a plus
• Communication: Excellent written and verbal communication skills, able to explain complex data concepts to both technical and non-technical audiences
• Collaboration: Strong interpersonal skills and the ability to work cross-functionally across Product, Engineering, and Analytics teams

Desirable

• As a Senior Data Engineer, you will own the design, build, and optimization of Pontera’s data platform - powering analytics, and data-driven product features
• At Pontera, the Data Engineer plays a crucial role in designing and overseeing all BI and analytics solutions. They collaborate closely with various departments such as Product, R&D, BizDev, and Executive teams to address their data analysis requirements. Additionally, they hold responsibility for essential financial and operational metrics
• This role offers the opportunity to make a significant impact in a fast-paced, high-growth environment while working on meaningful challenges that directly advance our mission
• At Pontera, we leverage a modern data stack that includes Snowflake, DBT, Python and Fivetran, with infrastructure-as-code and CI/CD best practices
• Design and maintain scalable data models and schemas in DBT/Snowflake to support analytical and operational workloads
• Build, optimize, and document robust ELT pipelines in SQL, Python, dbt for batch and near-real-time data ingestion
• Implement automated data-quality testing, monitoring, and alerting to guarantee trustworthy and timely data
• Collaborate with Product and Engineering teams on event instrumentation, schema design, and data governance standards
• Tune warehouse performance and manage cost efficiency through partitioning, clustering, and workload management
• Partner with Analytics and Data Science to translate business questions into engineered data solutions
• Mentor junior engineers and analysts, championing best practices in coding, documentation, and peer review