[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 arenaflex/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 arenaflex/CD context. • Experience with infrastructure-as-code (Terraform, CloudFormation) and arenaflex/CD platforms (GitLab arenaflex, 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.Apply Now

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