Job Description

We are seeking a highly skilled and motivated Data Technical Manager to lead our data engineering and analytics initiatives. The role involves managing technical teams, overseeing data platform development, ensuring data quality, and driving best practices for scalable, secure, and efficient data solutions. The ideal candidate will have a strong background in data engineering, cloud platforms, and people management, with the ability to align technical execution to business strategy.
Key ResponsibilitiesLead 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 QualificationsBachelor'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 QualificationsExperience 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.