[Hiring] DataOps Engineer @Sphere Partners

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.

Role Description

We are building a core data platform for a high-growth e-commerce company. The team needs to move from fragmented scripts and dashboards to a unified, automated, and trusted data foundation to support personalization and real-time analytics.
• Design and build automated CI/CD pipelines for data transformations, ETL/ELT, and ML model training.
• Implement a robust framework for data quality testing, validation, and proactive monitoring.
• Develop and maintain infrastructure-as-code templates for data pipeline orchestration and environment management.
• Establish and automate metadata collection, data lineage tracking, and pipeline observability.
• Create standards and tools to enable self-service data pipeline deployment for analytics and data science teams.

Qualifications
• Experience in building, automating, and maintaining data pipelines (5+ years).
• Experience with Python and SQL for engineering tasks.
• Experience with orchestration tools (Airflow, Dagster, Prefect) and modern data stack components.
• Proven track record of implementing data quality checks and testing in a CI/CD context.
• Experience with infrastructure-as-code (Terraform, CloudFormation) and CI/CD platforms (GitLab CI, GitHub Actions).

Requirements
• Practical experience implementing a DataOps methodology or internal data platform.
• Knowledge of data discovery and lineage tools (DataHub, Amundsen).

Nice to have
• Experience with Snowflake or BigQuery.
• Familiarity with Streamlit for building simple data apps.

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