Senior Data Engineer

About the role

We are looking for an experienced Senior Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake following a medallion architecture across bronze silver and gold layers. This role also uses AI tools like Claude and GitHub Copilot to speed up development.

What you will do

Design build and operate batch and streaming data pipelines on Databricks using PySpark Delta Lake and Databricks Workflows. Model and maintain a medallion (bronze/silver/gold) architecture serving analytics reporting and machine learning consumers. Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption. Use Claude or Github Copilot as a development accelerator generating code scaffolding writing and reviewing tests creating documentation and prototyping solutions. Write clean well-tested Python and SQL maintain high standards through code review and documentation. Optimize Spark jobs and Delta tables for performance and cost including partitioning clustering caching and cluster sizing. Implement data quality lineage and governance controls using Unity Catalog and automated validation checks. Debug troubleshoot and resolve pipeline failures data defects and production incidents. Participate in Agile or product-centric delivery practices including sprint planning and retrospectives. Collaborate with DevOps platform and analytics engineers on observability security and compliance best practices. Must haves 4+ years of professional experience in data engineering featuring direct expertise with Apache Spark and cloud-based data architectures. Strong hands-on experience building data pipelines with Databricks Apache Spark (PySpark) and Delta Lake. Advanced SQL and Python with strong data modeling skills across dimensional and Lakehouse patterns. Experience with streaming ingestion using Structured Streaming Auto Loader Kafka or Event Hubs. Experience with workflow orchestration (Databricks Workflows Airflow or Azure Data Factory). Experience with legacy platform migrations ETL modernization or managing data hygiene when porting old systems. Strong problem-solving collaboration and communication skills including mentoring junior engineers and explaining data concepts to non-technical stakeholders. Familiarity with Unity Catalog data governance access control and PII handling. Experience with dbt or an equivalent transformation framework. Familiarity with secure coding standards and industry security best practices. Experience delivering production data platforms at scale. Upper-intermediate English level. Nice to haves Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure Devops. Experience working with relational databases (specifically PostgreSQL) and data persistence concepts. Familiarity with logging and monitoring tools (e.g. Dynatrace CloudWatch Databricks system tables). Experience working in Agile or team-based development environments preferred. Perks and benefits Growth without limits build your skills through mentorship internal TechTalks challenging projects and a dedicated annual learning budget Competitive compensation get recognition that reflects your skills and impact with regular performance and compensation reviews Flexibility work 100% remotely with flexible hours that support focus autonomy and a healthy work rhythm Meaningful modern projects build impactful products using modern technologies alongside global teams and leading brands Collaborative culture join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized Well-being & support access local well-being programs and people-focused support tailored to your location

Job Type

Full-time

Work Location

Remote