Data Engineering Lead @ Net Connect

We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions.

If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team!

• Lead the design and implementation of scalable data pipelines using Databricks and PySpark
• Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems
• Work with product and analytics teams to gather and translate business data requirements into technical solutions
• Architect and optimize cloud-based data lakes and warehouses on AWS or Azure
• Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices
• Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows
• Ensure data integrity, security, and compliance across all solutions
• Collaborate cross-functionally with data scientists, analysts, and DevOps teams
• Drive performance tuning and operational excellence in deployed pipelines and data infrastructure
• Contribute to defining and executing the long-term data strategy for the organization

• 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure
• Strong programming skills in Python with good understanding of software engineering principles
• Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems
• Proven experience with cloud data lakes and data pipeline development in a production environment
• Expertise in building ETL/ELT workflows, including orchestration and automation
• Experience designing data models that support reporting, analytics, and machine learning
• Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git)
• Excellent problem-solving, analytical thinking, and communication skills
• Proven ability to lead and mentor technical teams in a collaborative environment

• Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse
• Understanding of data governance, lineage, and compliance practices
• Familiarity with Agile/Scrum methodologies
• Exposure to real-time streaming data technologies such as Kafka, Spark Streaming