ETL Developer

Position Overview: As an ETL Developer, you will be responsible for developing, maintaining, and optimizing ETL processes that handle large volumes of data. You will work closely with data engineers, analysts, and business stakeholders to deliver high-quality data solutions that meet the needs of our business. This is a fantastic opportunity for a driven professional to make a significant impact on the company’s data strategy. Experience - 5-8 years Key Responsibilities: • ETL Development & Optimization: Design, develop, and maintain efficient ETL processes for extracting, transforming, and loading data from various sources into structured data warehouses, data lakes, or other storage systems. • Data Integration: Work with cross-functional teams to integrate data from multiple sources (relational databases, flat files, APIs, cloud services, etc.) to create a unified view for analytics and reporting. • Data Quality & Transformation: Ensure data accuracy, consistency, and quality through effective data transformation techniques. Create data validation and cleansing procedures to improve data quality. • Performance Tuning: Monitor, optimize, and fine-tune ETL workflows to ensure high performance and low latency, even for complex data processing tasks. • SQL Expertise: Write, optimize, and troubleshoot complex SQL queries, stored procedures, and functions to manipulate and aggregate data. Ensure data integrity and optimal query performance. • Collaboration: Work closely with Data Architects, Data Engineers, and Business Intelligence teams to design data models and ensure alignment with business requirements and data strategies. • Data Governance & Security: Adhere to data governance standards, ensuring data privacy, security, and compliance throughout the ETL process. • Automation & Continuous Improvement: Leverage automation tools and best practices to improve ETL processes. Continuously seek opportunities for process optimization and efficiency gains. • Troubleshooting & Support: Troubleshoot and resolve issues related to data pipelines, data integrity, and job failures. Provide ongoing support and ensure minimal downtime. • Documentation: Document ETL processes, data mappings, and transformation logic for knowledge sharing and future maintenance. Required Skills & Qualifications: • Experience: 5-8 years of hands-on experience in ETL development and data integration in large-scale environments. • ETL Tools: Proficient in ETL tools like Informatica, Talend, Apache Nifi, SSIS, or similar platforms. • SQL Expertise: Advanced knowledge of SQL (including PL/SQL) with experience in writing complex queries, stored procedures, and optimizing query performance. • Data Warehousing: Strong understanding of Data Warehousing concepts and experience with Dimensional Modeling (Star Schema, Snowflake Schema). • Cloud Experience: Experience with cloud platforms like AWS, Azure, or Google Cloud (e.g., Redshift, BigQuery, S3, Azure Data Lake). • Programming Skills: Proficiency in at least one programming language (e.g., Python, Java, Shell Scripting) for ETL automation and custom transformations. • Big Data: Familiarity with Big Data technologies like Hadoop, Spark, and distributed processing frameworks is a plus. • Version Control & CI/CD: Experience with Git and CI/CD pipelines for version control and automated deployments. • Problem-Solving: Strong analytical and troubleshooting skills to identify and resolve complex data issues. • Soft Skills: Excellent communication, teamwork, and collaboration skills. Ability to work independently and handle multiple projects concurrently. Desirable Skills: • Experience with NoSQL databases like MongoDB, Cassandra, or HBase. • Knowledge of Data Lake architectures and associated technologies. • Familiarity with Data Governance, Data Privacy, and Compliance standards. • Experience in Agile development methodologies (Scrum, Kanban, etc.). Education & Certifications: • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. • Relevant certifications in ETL tools (e.g., Informatica, Talend), cloud platforms, or Data Engineering are a plus.