Tech Lead Databricks Data Engineer

Mitre Media is redefining FinTech with AI-driven tools that empower millions of investors. Our portfolio, including Dividend.com and MutualFunds.com, leverages LLMs to deliver novel data insights and visually rich user experiences. For over a decade, we’ve served individual investors, financial advisors, and top asset managers like BlackRock and Vanguard through our premium data, tools, and advertising solutions. If you’re excited by the intersection of big data, AI, and investing, join our lean, entrepreneurial team from anywhere within ±3 hours of Eastern Time.

As Tech Lead Data Engineer, you’ll architect and maintain the data backbone powering every feature across our product suite. Reporting to the CTO, you will design Databricks-based ETL pipelines, model complex investment data, and surface low-latency, high-quality datasets for both user-facing features and internal AI/analytics workloads. You’ll collaborate in a remote-first hybrid culture that values in-person “bursts” of collaboration, follow ShapeUp for project planning, and ship pragmatic solutions that favor de-scoping over delays.

• Design, implement, and optimize large-scale ETL workflows in Databricks (Apache Spark, Delta Lake, DBT).

• Develop algorithms that transform raw market data into actionable insights.

• Own data quality and lineage, instituting tests, monitoring, and alerting for mission-critical pipelines.

• Evolve our cloud data platform (AWS & GCP) for scale, performance, and cost efficiency.

• Mentor engineers, championing best practices in code reviews, documentation, and DevOps for data.

• Programming: Expert in Python plus working knowledge of Scala or Java.

• Databricks & Spark: Hands-on with cluster tuning, job orchestration, and Delta Tables.

• SQL & DBT: Strong analytical SQL, modular data-model design, and CI/CD for transformations.

• Cloud: Production experience on AWS or GCP data services (e.g., S3/GCS, EMR/Dataproc, Glue/Dataflow).

• ETL & Orchestration: Solid grasp of EL(T) patterns, workflow scheduling, and incremental processing.

• Data Modeling: Dimensional and schema-on-read designs for analytics and AI.

• Building feature stores or inference-ready tables for ML/LLM workflows.

• Familiarity with vector databases or embedding pipelines

• Apache Airflow, Luigi, or Dagster for DAG orchestration.

• Experience with Looker, Tableau, or Stripe’s Vizier-style visualization stacks.

• Financial-markets domain knowledge (equities, ETFs, mutual funds).

• Machine-learning engineering or statistical-analysis background.

• Entrepreneurial mindset with a passion for AI and FinTech innovation.

• Self-starter who diagnoses problems, proposes trade-offs, and delivers.

• Clear communicator who thrives in distributed, cross-functional teams.

• Mentorship attitude—uplifts peers through code reviews and knowledge-sharing.

• Detail-oriented and disciplined about data accuracy and documentation.

• Impactful Work – Your pipelines feed every insight we deliver to millions of investors.

• Cutting-Edge Tech – Databricks, Delta Lake, LLMs, Hotwire, and xAI’s API, all in a modern microservices stack.

• Autonomy & Influence – Work directly with the CEO & CTO to shape our data and AI strategy.

• Competitive Compensation – $150k – $185k CAD/USD plus benefits and performance bonuses.

• Remote Flexibility – Remote-first within ±3 hrs ET; optional collaboration hubs in Toronto and NYC.

• Growth Opportunities – Budget for conferences (e.g., Data+AI Summit, NeurIPS) and continuous learning.

Mitre Media powers premium financial brands like Dividend.com and MutualFunds.com with the Mitre Platform. This platform integrates traditional content management, financial data, first-party data, ad revenue, and subscription tools, all enhanced by LLMs for rich, user-focused experiences. Our data-derived insights delight users, while our advertising solutions deliver unmatched performance for partners like BlackRock and Vanguard, leveraging advanced targeting and first-party data.

Submit your resume, GitHub profile, and a brief note on why you’re excited about building AI-driven FinTech to [email protected].