[Hiring] Senior Data Platform Engineer @isolved

Role Description

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.

• 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.

Qualifications

• Bachelor's degree in computer science, software engineering, information systems, or related field, or equivalent practical experience.
• 5+ years of hands-on experience in data platform engineering, infrastructure engineering, data engineering, or a closely related discipline.
• Seasoned customer engagement experience; professional services experience a huge plus.
• Deep, hands-on experience administering Databricks, including Unity Catalog, cluster policies, service principals, secrets management, and cost optimization.
• Deep, hands-on experience administering Snowflake, including warehouses, roles/RBAC, resource monitors, and secure data sharing.
• Deep experience building and maintaining Fivetran connectors and incremental ingestion pipelines.
• Deep experience with dbt, including models, tests, documentation, and CI integration.
• Deep experience building and maintaining Workato recipes and integration workflows.
• Strong CI/CD experience, ideally with GitHub Actions, including automated testing and deployment pipelines.
• Strong Terraform experience provisioning and managing cloud and data platform resources as code.
• Strong PySpark experience for large-scale data processing, and solid Python skills for automation and internal tooling.
• Working knowledge of Azure and/or AWS cloud infrastructure.
• Comfort with Git-based version control and collaborative development workflows.
• Strong troubleshooting, root-cause analysis, and incident response skills.
• Ability to operate effectively within architectural standards set by others, while still contributing ideas and technical judgment to architecture discussions.
• Strong communication skills and the ability to work cross-functionally with architects, data engineering, analytics, and integrations teams.

Requirements

• Typically requires a minimum of 6 years of related experience with a bachelor's degree; 6 years and a master's degree; or equivalent experience.

Benefits

• Comprehensive list of employee total rewards offerings.