Design and build robust, highly scalable data pipelines and lakehouse infrastructure with PySpark, Databricks, and Airflow on AWS.
Improve the data platform development experience for Engineering, Data Science, and Product by creating intuitive abstractions, self‑service tooling, and clear documentation.
Own and maintain core data pipelines and models that power internal dashboards, ML models, and customer-facing products.
Own the Data & ML platform infrastructure using Terraform, including end‑to‑end administration of Databricks workspaces: manage user access, monitor performance, optimize configurations (e.g., clusters, lakehouse settings), and ensure high availability of data pipelines.
Lead projects to improve data quality, testing, observability, and cost efficiency across existing pipelines and backend systems (e.g., migrating Databricks SQL pipelines to dbt, scaling data ingestion, improving data-lineage tracking, and enhancing monitoring).
Act as the primary engineering partner for the Data Science team—embedded closely to gather requirements, design scalable solutions, and provide end-to-end support on all engineering aspects of their work.
Work closely with backend engineers and data scientists to design performant data models and support new product development initiatives.
Share best practices and mentor other engineers working on data-centric systems.

4+ years of experience in software engineering with a strong background in data infrastructure, pipelines, and distributed systems.
Advanced proficiency in Python and SQL.
Hands-on Spark development experience.
Expertise with modern cloud data stacks—AWS (S3, RDS), Databricks, and Airflow—and lakehouse architectures.
Hands‑on experience with foundational data‑infrastructure technologies such as Hadoop, Hive, Kafka (or similar streaming platforms), Delta Lake/Iceberg, and distributed query engines like Trino/Presto.
Familiarity with ingestion frameworks, developer‑experience tooling, and best practices for data versioning, lineage, partitioning, and clustering.
Strong problem-solving skills and a proactive attitude toward ownership and platform health.
Excellent communication and collaboration skills, especially in cross-functional settings.

Senior Software Engineer, Data Platform

Key skills