Location: Hybrid, Iselin, NJ About the Team: Our Data Ops team empowers data-driven features across Factorial by providing advanced ingestion services (SaaS APIs, DBs, Streams), storage capabilities (Data Lake, Stream Storage), data quality, and governance.
As a Senior Data Engineer, you will expand this mission by reinforcing our analytics realm. You will leverage data engineering best practices to implement and maintain robust, scalable data pipelines and processes. You will be part of a small, high-agency team driving the design and operation of data infrastructure that supports product developers, making data a core asset that powers both internal analytics and user-facing product features.
We predominantly use Python and operate with a GitOps-driven mindset, running short development cycles with ephemeral dev environments to test, fail fast, and iterate quickly.
Responsibilities: - Take end-to-end ownership of Lakehouse components from design to deployment, applying best practices in batch and streaming, and partnering directly with Infrastructure to operate scalable analytical systems.
- Collaborate with Data Ops and Product teams to integrate data from various sources, design efficient data flows, and enhance our existing analytics platform with robust dashboards and self-service capabilities.
- Write RFCs, lead technical conversations, and share knowledge while mentoring less-experienced engineers, especially Analytics Engineers working within the Lakehouse framework.
- Engage with stakeholders from managers to product teams, translating monitoring and analytics requirements into actionable projects with high-quality deliverables.
- Active participation in team rituals, pairing with different domains to understand their data challenges, and continuously experimenting to improve how data is ingested, curated, and exposed.
Experience: - Bachelor's or Master's degree in Computer Science, Information Technology, or a related field with 5+ years of experience.
- Solid experience building and operating reliable data pipelines, with a strong focus on analytics transformation and Lakehouse best practices.
- Experience working with distributed processing and query engines such as Apache Spark and Trino.
- Proven track record of implementing dbt in production environments, including advanced modeling, testing, and documentation.
- Hands-on experience working with Apache Iceberg in production environments.
- Experience with Iceberg catalogs such as Polaris, Lakekeeper, or similar solutions for table governance and metadata management.
- Experience with data ingestion tools such as Fivetran, Airbyte, or similar ELT/ETL platforms.
- Familiarity with AWS cloud services.
- Comfort working entirely in English and collaborating within distributed teams.
Preferred Qualifications: - Strong knowledge of Terraform and infrastructure concepts, including experience with IaC and cloud resource provisioning.
- Experience designing and implementing Generative AI agents, including hands-on experience with frameworks such as LangChain.
As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location. Pay ranges for candidates in locations other than New York City, may differ based on the local market data in that region.
The salary range for positions that will be physically based in New Jersey is $96,000-$128,000.
Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year.
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