Senior Data Engineer / Development Lead

Position Overview We are seeking a highly qualified Senior Data Engineer / Development Lead with deep technical expertise in modern data engineering, multi cloud architecture, and scalable system build. This role requires hands-on development capability, strong architectural thinking, and leadership in delivering enterprise-grade data solutions. Key Responsibilities Lead the design and development of robust data engineering solutions using Python, Microsoft Fabric, Snowflake, and Databricks. Architect and deliver multi-cloud data platforms (preferred: Azure and AWS) with a focus on scalability, security, and performance. Build and optimize ETL/ELT workflows, including support for CDC, CDF, batch, streaming, and near real-time pipelines. Develop, integrate, and maintain REST APIs to support data ingestion, interoperability, and automation. Design and maintain CI/CD pipelines using modern DevOps tools. Provide technical leadership including code reviews, mentorship, architectural guidance, and standard methodologies. Collaborate with multi-functional teams, architects, and leadership to deliver high-quality solutions aligned with business goals. Continually explore emerging data engineering, AI, and cloud technologies to enhance platform capabilities. Required Qualifications (Must-Have) 10+ years of hands-on software development and data engineering experience. Strong expertise in Python for data engineering, automation, and application development. In-depth experience with Microsoft Fabric (Data Factory, Lakehouse, Warehouse, Real-Time). Hands-on experience in multi-cloud environments (Azure and AWS preferred). Strong proficiency with Snowflake, including Snowpipe, Streams, Tasks, and performance tuning. Deep experience with Databricks (SQL, Python, Delta Lake, Unity Catalog, pipelines/workflows). Proficiency in building and consuming REST APIs. Hands-on expertise with CI/CD pipelines (Azure DevOps, GitHub Actions, GitLab etc.). Experience with containerization and orchestration technologies, including Docker and Kubernetes. Strong SQL and NoSQL database experience. Excellent debugging, performance optimization, and production support skills. Strong interpersonal skills with shown experience leading and mentoring engineering teams. Preferred / Nice-to-Have Skills Exposure to or foundational understanding of AI/ML concepts, feature engineering, or model lifecycle. Experience with data governance and metadata tools (Purview, Unity Catalog, etc.). Knowledge of workflow orchestration platforms (Fabric Data Pipelines, Airflow, ADF). Understanding of data security, encryption standards, RBAC, and cloud compliance. Preferred Education Background Minimum: Bachelor’s degree or equivalent experience in Engineering or Computer Science. Cloud certifications such as Azure, AWS, GCP, Databricks, or Snowflake are a plus. Soft Skills Strong leadership and team mentoring capabilities. Effective communication and collaborator leadership skills.