Senior Manager - Data Engineering

What You'll Do

• Lead, mentor, and develop a team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.
• Design, build, and maintain scalable data pipelines and architectures for optimal data extraction, transformation, and loading (ETL).
• Work closely with product managers, analysts, and other stakeholders to ensure data availability and quality for analytical and operational needs.
• Find opportunities to automate data processes and improve data quality and reliability.
• Assess and incorporate data management tools, technologies, and standard methodologies.
• Oversee data engineering projects from conception to delivery, ensuring alignment with business goals and timelines.
• Ensure data governance, security, and compliance with industry regulations and company policies.

What You Need to Succeed

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience (15+ years) in data engineering or related roles, with at least 5+ years in a leadership or managerial position.
• Proficient in writing complex SQL queries across multiple databases (e.g., SQL Server, Azure, MySQL) to efficiently extract, transform, and analyze data.
• Hands on experience in data engineering tools and technologies such as Python, Databricks, PySparkSQL, Synapse, SSIS, Azure Data Factory, or similar technologies. 
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark)
• Proficient in Microsoft Power Platform, including Power BI, Power Apps, and Power Automate, to deliver integrated data-driven solutions.
• Demonstrated experience in AI and Machine Learning, with a focus on Generative AI (GenAI) use cases in data engineering, including automating data pipelines and enhancing data quality and analytics.
• Familiarity with DevOps practices and CI/CD pipelines for data engineering.
• Demonstrated success in managing large-scale data infrastructure and data pipeline projects.
• Familiarity with data governance, data quality frameworks, and data security practices.
• Strong leadership skills with the ability to inspire and guide a team.
• Strong communication skills to effectively communicate complex data concepts to technical and non-technical collaborators.
• Strong problem-solving skills and the ability to think strategically about data solutions.
• A passion for leveraging data to drive business insights and outcomes.