Senior Data Platform Engineer (Python)

Location: Remote

Company

hirify.global delivers data engineering capabilities for client projects.

What you will do

• Build and maintain scalable Python and SQL data pipelines orchestrated with Airflow and delivered to S3-backed data lakes and Redshift/Athena warehouses.
• Design lakehouse architectures using Apache Iceberg and Delta Lake.
• Implement data quality frameworks, data contracts, schema evolution, monitoring, alerting, SLIs, and SLOs.
• Optimize large-scale batch and streaming workloads with Spark/PySpark and dbt across gigabytes to terabytes of data.
• Develop infrastructure as code and CI/CD practices for repeatable, testable, and observable data workflow deployments.
• Collaborate with analytics, product, and engineering stakeholders to turn raw data into dependable platform capabilities.

Requirements

• 5+ years of experience designing and building production ETL/ELT pipelines at scale.
• Hands-on expertise with Python, advanced SQL, and data modeling.
• Production experience with Airflow, data transformation, and Apache Spark/PySpark optimization.
• Practical AWS experience across S3 and data warehouses.
• CI/CD experience including Git, testing, and deployment automation.
• Experience building data quality frameworks, data contracts, and schema evolution strategies.

Nice to have

• Experience with modern table formats, medallion architecture, dbt, streaming platforms, and data observability tooling.

Culture & Benefits

• Remote data engineering contract.
• Work spans batch and streaming workloads with analytics, product, engineering, and client stakeholders.

Hiring process

• Brief non-technical conversation about background, career aspirations, communication, teamwork, and decision-making.
• 60–90-minute technical interview focused on skills relevant to the client’s requirements.
• Final client interview followed by an offer after successful completion.