Role : Senior Data Platform Engineer, P4

Summary/objective :

The Senior Data Platform Engineer is a hands-on technical owner of isolved's data platform infrastructure and day-to-day operations, working within the architectural vision set by the data architecture team.

This role carries a lighter architectural mandate, though architectural thinking is still highly valued, in exchange for deeper, more hands-on ownership of the systems that keep the platform running : administering and tuning Databricks and Snowflake, building and maintaining Fivetran, dbt, and Workato pipelines and integrations, and operating CI/CD and infrastructure-as-code practices in Terraform and GitHub Actions.

This person is the engineer who configures, monitors, troubleshoots, and continuously improves isolved's data systems on a daily basis, escalating and partnering with the architects on larger design decisions while owning execution end to end.

Core Job Duties :

- Administer and tune Databricks workspaces on a day-to-day basis, including Unity Catalog, access controls, service principals, cluster policies, secrets management, and cost optimization.

- Administer and tune Snowflake on a day-to-day basis, including warehouses, roles and RBAC, resource monitors, and secure data sharing configuration.

- Build, monitor, and maintain Fivetran connectors and incremental ingestion pipelines, troubleshooting sync failures and data quality issues as they arise.

- Build, test, and maintain dbt models, tests, and documentation, keeping transformation pipelines reliable and well-governed.

- Write and maintain Terraform modules to provision and manage Databricks, Snowflake, and cloud infrastructure (AWS and/or Azure) as code.

- Build and maintain CI/CD pipelines, primarily in GitHub Actions, to automate testing, deployment, and infrastructure changes across the data platform.

- Write PySpark and Python code to build, optimize, and maintain data processing jobs and internal automation tooling.

- Monitor platform and pipeline health, troubleshoot issues, and lead or support incident response and root-cause analysis for the data platform.

- Implement identity, access, and security controls (e.g., IAM, RBAC, secrets management) in line with standards set by the principal architects.

- Support pipeline orchestration (e.g., Airflow or equivalent) to sequence and monitor data workflows across ingestion, transformation, and delivery.

- Configure, maintain, and enhance data visualization tools like Power BI.

- Contribute to architecture discussions, documentation, and standards under the guidance of the Principal Platform Architect and Principal Data Architect, without owning target-state architecture directly.

- Partner with data engineering, data analytics, and the integrations team to translate architectural standards into working, well-operated systems.

- Identify opportunities to improve platform reliability, automation, and cost efficiency, and raise architectural implications to the principal architects when they extend beyond day-to-day execution.

- Document architectural diagrams, operational runbooks, configurations, and troubleshooting guides for the systems you own.

Minimum Qualifications :

- Bachelor's degree in computer science, software engineering, information systems, or related field, or equivalent practical experience.

- 6+ years of hands-on experience in data platform engineering, infrastructure engineering, data engineering, or a closely related discipline.

- Deep, hands-on experience administering Databricks, Snowflake, Fivetran, dbt, and Workato.

- Strong CI/CD experience, ideally with GitHub Actions, and Terraform experience.

- Strong PySpark experience for large-scale data processing, and solid Python skills.

- Working knowledge of Azure and/or AWS cloud infrastructure.

- Strong troubleshooting, root-cause analysis, and incident response skills.