[Hiring] Senior Data Engineer @Protective

Role Description

The work we do has an impact on millions of lives, and you can be a part of it. We help protect our customers against life’s uncertainties. Regardless of where you work within the company, you’ll be helping provide protection and peace of mind when our customers need it most.

Protective is looking for Data Engineers to design, build, and operate production data pipelines on Voyager, our Databricks lakehouse on Azure. You will own the end-to-end flow of data through a medallion architecture — ingesting source data into the Bronze layer, applying cleansing, validation, and conformance in Silver, and publishing trusted, consumption-ready data products in Gold.

This role sits at the intersection of engineering, analytics, and platform operations. You will write production-grade Python and SQL, enforce data contracts, and help Protective treat data as a product with named owners and real consumers. You will be embedded on a delivery pod that owns its data products end to end, rather than servicing tickets from a queue.

On Voyager, the medallion layers are named Raw, Prep, and Prod. They map directly to Bronze, Silver, and Gold and are used interchangeably in this description.

Key Responsibilities

• Design, develop, and maintain production data pipelines on Databricks using Python, SQL, Apache Spark, and Delta Lake.
• Build Bronze-layer ingestion that reliably captures data from APIs, relational databases, flat files, cloud storage, and SaaS platforms.
• Develop Silver-layer transformations in dbt and Python over Delta Lake that cleanse, standardize, type, deduplicate, validate, conform, and enrich data.
• Create Gold-layer data products: dimensional models, slowly changing dimensions, fact and bridge tables, aggregates, and serving tables.
• Produce and maintain the curated datasets ML engineering trains and serves models from.
• Author and maintain data contracts using the Open Data Contract Standard (ODCS).
• Implement data quality as code.
• Orchestrate ingestion and transformation as assets in Dagster.
• Apply governance through Unity Catalog.
• Implement incremental and merge-based processing with Delta Lake.
• Troubleshoot production failures, data-quality issues, source-system changes, and late-arriving or duplicate data.
• Build and maintain CI/CD for data assets in Azure DevOps.
• Instrument what you own for observability.
• Work inside the platform’s control expectations.
• Participate in code review and document architecture, runbooks, and data products.
• Work with data architects, analysts, product owners, and business stakeholders to translate requirements into maintainable data solutions.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; equivalent practical experience considered.
• 3+ years building and supporting production data pipelines in a cloud data platform environment.
• Strong hands-on Python and SQL.
• Hands-on experience with Databricks or a comparable Spark-based lakehouse.
• Practical understanding of medallion / multi-layer lakehouse design.
• Experience ingesting data from APIs, relational databases, files, or SaaS applications.
• Working knowledge of dimensional modeling and ELT design patterns.
• Experience with orchestration and scheduling using Dagster, Databricks Workflows, Airflow, Azure Data Factory, or similar.
• Git-based source control, pull request review, automated testing, and CI/CD as normal practice.
• Experience troubleshooting production data failures, performance bottlenecks, and source-system changes.
• Experience with pipeline monitoring and alerting.
• Ability to explain technical designs and trade-offs to both technical and non-technical partners.

Preferred Qualifications

• Databricks certification (Data Engineer Associate or Professional) or equivalent demonstrated depth.
• Unity Catalog experience.
• dbt on Databricks, or another transformation framework used alongside Spark.
• Python-based modeling frameworks over Delta Lake.
• Experience with a declarative Python ingestion framework such as dlt (dltHub), Airbyte, Meltano, or Fivetran.
• Dagster experience specifically.

Benefits

• Comprehensive health, dental, and vision insurance.
• Mental health benefits and an employee assistance program.
• Variety of paid time away benefits (e.g., paid time off, paid parental leave, short-term disability, and a cultural observance day).
• Contributions to healthcare accounts, a pension plan, and a 401(k) plan with Company matching.
• Engagement in ProHealth Rewards, Protective’s platform to improve wellbeing while earning cash rewards.

Salary Information

Protective’s targeted salary range for this position is $84,000 to $128,667. Actual salaries may vary depending on factors, including but not limited to, job location, skills, and experience.

This position also offers additional incentive opportunities through an annual incentive based on individual and Company performance.

Accommodations for Applicants with a Disability

If you require an accommodation to complete the application and recruitment process due to a disability, please email [email protected] . This information will be held in confidence and used only to determine an appropriate accommodation for the application and recruitment process.

Please note that the above email is solely for individuals with disabilities requesting an accommodation. General employment questions should not be sent through this process.

We are proud to be an equal opportunity employer committed to being inclusive and attracting, retaining, and growing an inclusive workforce.