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About the role
Job Summary IntelliCredence Pvt. Ltd. is looking for an experienced Lead Data Engineer / Data Platform Lead to design, build, and optimize scalable enterprise data platforms. The ideal candidate should have strong hands-on experience with up-to-date cloud data technologies such as Microsoft Fabric, Azure Databricks, Snowflake, Power BI, Python, PySpark, and SQL. The role requires a combination of technical expertise, data architecture knowledge, leadership capability, and experience delivering secure and high-performance data solutions. The selected candidate will lead data engineering initiatives, define technical standards, mentor team members, and work closely with business stakeholders, analysts, and data science teams. Key Responsibilities - Lead the design, development, and implementation of scalable data pipelines, data models, and ETL/ELT processes. - Architect and optimize enterprise data lake, lakehouse, and data warehouse solutions. - Build modern data platforms using Microsoft Fabric, Databricks, Snowflake, or related cloud technologies. - Design batch and real-time data-processing workflows. - Develop and optimize complex SQL queries, stored procedures, and data-transformation logic. - Enable business analytics and self-service reporting through Power BI and other visualization tools. - Create efficient semantic models and datasets for enterprise reporting. - Collaborate with data scientists, analysts, application teams, and business stakeholders to understand data requirements. - Ensure reliability, scalability, performance, and availability of data solutions. - Implement data-quality checks, governance standards, security controls, and access-management practices. - Establish coding standards, architecture guidelines, documentation practices, and reusable frameworks. - Implement CI/CD pipelines for data engineering and analytics solutions. - Monitor and optimize data pipelines, Spark jobs, warehouse performance, and cloud-resource usage. - Troubleshoot data-processing, integration, and performance-related issues. - Mentor junior and mid-level data engineers and provide technical guidance to the team. - Evaluate emerging technologies and recommend improvements to the existing data ecosystem. Required Qualifications - Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related field. - 7+ years of experience in data engineering, data platform development, or data architecture. - At least 2-3 years of experience in a technical lead, data lead, or architect role. - Strong hands-on experience with at least one of the following platforms: - Microsoft Fabric - Azure Databricks - Snowflake - Strong proficiency in SQL. - Hands-on programming experience in Python, PySpark, or Scala. - Experience designing ETL/ELT pipelines and large-scale data-processing solutions. - Strong understanding of dimensional modelling, star schemas, data lakes, lakehouses, and data warehouses. - Experience with cloud platforms such as Microsoft Azure, AWS, or GCP. - Experience working with structured, semi-structured, and unstructured data. - Knowledge of data governance, security, data quality, lineage, and access-control practices. - Experience with CI/CD, Git, Azure DevOps, GitHub, or similar tools. - Strong troubleshooting, performance-optimization, and problem-solving skills. - Ability to lead technical discussions and communicate effectively with business and technical stakeholders. Experience: 7+ Years Employment Type: Full-time Position Level: Lead Notice Period: Immediate joiners preferred .
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