Technical Manager

• Lead and manage a team of data engineers, analysts, and developers to deliver high-quality data solutions.
• Oversee the design, development, and maintenance of data pipelines, data lakes, and data warehouses.
• Ensure data availability, reliability, scalability, and performance across platforms.
• Collaborate with business stakeholders to understand requirements and translate them into technical solutions.
• Establish data governance, security, and compliance best practices.
• Drive continuous improvement in data engineering processes, tools, and standards.
• Provide technical guidance, mentoring, and career development for team members.
• Manage project timelines, resource allocation, and delivery milestones.
• Partner with cross-functional teams (BI, Product, IT, and Cloud teams) to enable data-driven decision-making.
• Stay updated with emerging technologies, tools, and trends in data engineering and cloud ecosystems.
  

Required Skills And Qualifications

• Bachelor's or master's degree in computer science, Data Engineering, Information Systems, or a related field.
• 8+ years of experience in data engineering or related fields, with at least 3+ years in a leadership/management role.
• Strong expertise in SQL, data modeling, and ETL/ELT processes.
• Hands-on experience with cloud data platforms (Azure) and tools such as Databricks, Snowflake
• Proficiency in modern data tools and frameworks (Spark, Kafka, Airflow etc.).
• Knowledge of data governance, data security, and compliance (GDPR, HIPAA, etc.).
• Strong leadership, problem-solving, and communication skills.
• Proven ability to manage multiple priorities in a fast-paced environment.
• Proven experience in setting up and orchestrating Databricks pipelines, including automated workflows and job scheduling.
• Strong hands-on knowledge of Databricks Unity Catalog, Hive Metastore, and the ability to build and manage Databricks Dashboards for data visualization and monitoring.
• Working experience with Azure Functions for serverless data processing and event-driven workflows.
• Proficient in implementing Medallion Architecture (Bronze, Silver, Gold layers) for scalable and structured data ingestion, transformation, and delivery.
• Experience in building end-to-end data pipelines on Azure and Databricks environments.
• Good to have: Familiarity with Box for data integration and Databricks Asset Bundles (DAB) for managing and deploying reusable code artifacts.
  

Preferred Qualifications

• Experience with Machine Learning pipelines and MLOps.
• Familiarity with BI/visualization tools (Power BI, Tableau, Looker).
• PMP, Scrum Master, or Agile delivery experience.
• Prior experience managing hybrid on-premise and cloud data solutions.