Mogi I/O is seeking a Senior Data Engineer to design and implement scalable data solutions for analytics in a cloud-based environment. The role involves collaborating with cross-functional teams to optimize data pipelines and ensure data quality.
Job Overview A global broadcasting and entertainment technology leader is seeking a Senior Data Engineer to design and implement data solutions supporting key business KPIs and analytics. The role involves building scalable data pipelines, optimizing data models, and automating quality checks in a cloud-based ecosystem. You’ll collaborate with business, analytics, and infrastructure teams to deliver high-performance, reliable, and data‑driven systems across the enterprise. Key Responsibilities • Partner with cross‑functional teams to define, design, and implement end‑to‑end data pipelines. • Architect scalable data solutions leveraging Snowflake, Spark, Databricks, and cloud services (AWS/Azure/GCP). • Build and maintain robust ETL workflows using orchestration tools such as Airflow or Prefect. • Develop automated data quality checks and ensure system reliability. • Design and manage data models using dimensional modeling and normalization principles. • Optimize SQL queries and ETL performance for analytical workloads. • Implement CI/CD for data pipelines and database deployments using Schema Change and related tools. • Conduct ad hoc analyses and ensure high‑quality data for reporting and analytics. • Collaborate with business stakeholders to translate data into actionable insights. Must‑Have Requirements • 5+ years of experience in Data Engineering with strong hands‑on technical expertise. • Advanced proficiency in SQL, data modeling (dimensional, normalized), and performance tuning. • Experience with Spark, Snowflake, Python, and orchestration tools (Airflow or Prefect). • Exposure to at least one cloud platform (AWS, Azure, or GCP). • Strong analytical reasoning and strategic problem‑solving abilities. • Excellent communication skills and experience working in agile, cross‑functional teams. Nice‑to‑Have Skills • Experience with Kafka and data integration tools such as Datorama, Improvado, or Five Tran. • Familiarity with CI/CD pipelines (Jenkins, Git Hub Actions) and containerization using Docker. • Knowledge of monitoring tools like Datadog. • Exposure to AI or data‑driven automation frameworks. Preferred Qualifications • Bachelor’s or Master’s degree in Computer Science, Engineering, or related fields. • Experience in the Media or Entertainment industry or similar high‑volume data environments. • Strong understanding of market and consumer data analytics. Location USA – Santa Monica / Los Angeles / New Jersey / Seattle, WA Work Type Full‑Time (Hybrid – 4 Days On‑site) Experience Required 5–14 Years in Data Engineering Compensation USD 100,000 – 140,000 Annual Eligibility US Citizen or Green Card Holder #J-18808-Ljbffr
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