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We are looking for a highly motivated and experienced Implementation/Technical Lead to oversee the end-to-end deployment and operationalization of our Privates data platform. The ideal candidate will need to have a strong background in data engineering, platform architecture, sound technical knowledge on full stack technologies - Java/Python and will work on diverse projects from building APIs and web applications to data processing and automation around the data platform while ensuring alignment with business and technical requirements. This role requires Java/Python programming and related frameworks along with strong data engineering and problem solving skills mindset.
Job Responsibility:
Architect, develop, and deploy scalable and reliable data pipelines, storage solutions, and analytical tools on Azure and Snowflake
Ensure platform scalability, reliability, and security to meet current and future business needs
Implement and manage data lakes, warehouses, and ELT/ETL processes
Lead code reviews, enforce development best practices, and drive continuous improvement within the team
Integrate real-time and batch data processing capabilities
Implement and enforce data governance policies, security protocols, and regulatory requirements
Establish robust data quality, lineage, and cataloging processes
Develop and integrate APIs and backend systems using frameworks like Django, Flask, or FastAPI
Create scripts and tools for data analysis, transformation, and automation
Write and execute unit and integration tests and perform debugging to ensure software quality
Collaborate effectively with developers, product managers, business analysts, and other stakeholders
Translate business requirements into scalable technical solutions
Manage code deployments through CI/CD pipelines and utilize GitHub for version control
Requirements:
Proven experience leading the design and development of large-scale data platforms
Demonstrated experience as a full-stack developer (or similar role) with strong Java/Python skills
Deep expertise in data platform technologies, including Snowflake and Azure SQL Server
Proficiency with data engineering tools and frameworks like Apache Kafka and Spark
Strong understanding of cloud platforms (Azure) and containerization (Docker, Kubernetes)
Experience with both batch and real-time data processing
Extensive knowledge of SQL and programming languages (Java/Python)
Excellent problem-solving, communication, and leadership skills
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