Manager, Data Science

Your responsibilities will include Collaborate with data architects, ETL developers, engineers, BI developers/data scientists, and information designers to identify and define required data structures, formats, pipelines, metadata, and workload orchestration capabilities. Provide thought leadership and new perspectives on how to leverage GCP cloud services and capabilities. Design, develop, and maintain scalable ETL/ELT pipelines to support data ingestion, transformation, and integration from various sources. Build and manage data warehouses, data lakes, and streaming platforms. Ensure data quality, integrity, and governance through validation, monitoring, and automation. Collaborate with stakeholders to understand business requirements and translate them into data solutions. Implement best practices for data security, compliance, and privacy. Troubleshoot data issues and support downstream analytics and reporting needs. Experience in product and/or data architecture and data engineering. Bachelor's degree or higher in STEM fields such as Computer Science, Information Management, Big Data & Analytics, or equivalent work experience. Hands-on experience in designing and implementing creative data solutions using GCP (BigQuery, Dataflow, Dataproc, Pub/Sub, Spark/PySpark, Python, SQL, etc.). Strong background in architecting solutions for data extraction, transformation, and loading from a variety of structured, unstructured, and semi-structured sources using SQL, NoSQL, and data pipelines for real-time, streaming, batch, and on-demand workloads. Solid understanding of Agile SDLC implementation in public cloud ecosystems, including environment management, test automation, CI/CD, and resource optimization. Experience in analytics/data management strategy, architectural blueprinting, business case development, and effort estimation for GCP-based analytics solutions. Knowledge of GCP services (BigQuery, DataFlow, Cloud Functions, Cloud Run, GCS) is a plus. Experience with software configuration management tools such as JIRA, Git, Jenkins, Bitbucket, and Confluence. Familiarity with Data Analytics tools such as Tableau and Looker. Proven experience as a Data Engineer or in a similar role. Proficiency in SQL and at least one programming language (Python, Java, Scala, etc.). Hands-on experience with cloud platforms (AWS, GCP, or Azure) and data services (Redshift, BigQuery, Snowflake, Databricks, etc.). Strong knowledge of data modeling, data warehousing concepts, and distributed systems. Experience with workflow orchestration tools (Airflow, Prefect, Luigi, etc.). Familiarity with streaming technologies (Kafka, Kinesis, Spark Streaming, Flink, etc.). Understanding of CI/CD pipelines, DevOps practices, and version control systems (Git). Excellent problem-solving, communication, and teamwork skills. Background in CPG/Retail or eCommerce. GCP Data Engineering or Cloud Architect Certification. Full stack development is a plus. Experience with machine learning pipelines or supporting data science workflows. Knowledge of data governance frameworks (GDPR, HIPAA, etc.). Familiarity with containerization and orchestration (Docker, Kubernetes).