ETL Developer

Job Title: ETL Developer

Location: [Remote]

Job Type: Full-Time

Job Overview:

We are seeking an experienced ETL Developer with 5+ years of hands-on experience in developing, implementing, and maintaining Extract, Transform, Load (ETL) processes to support data integration, processing, and analysis. The ideal candidate will have expertise in ETL tools, data warehousing concepts, and a deep understanding of databases, SQL, and cloud technologies.

You will work closely with cross-functional teams, including Data Engineers, Data Analysts, and Business Intelligence teams, to ensure that data pipelines are efficient, reliable, and scalable.

Key Responsibilities:

• ETL Development:
• Design, develop, and maintain ETL pipelines to extract data from various source systems, transform it based on business logic, and load it into data warehouses or lakes.
• Optimize ETL workflows to ensure high-performance data processing and minimize data latency.
• Data Integration:
• Integrate data from multiple sources, including relational databases, flat files, cloud platforms (AWS, Azure, GCP), APIs, and third-party systems.
• Implement complex transformations and business rules to ensure data consistency and accuracy.
• Data Quality & Validation:
• Implement data validation, quality checks, and error-handling mechanisms within the ETL processes.
• Perform data profiling to understand data quality issues and recommend solutions for data cleansing.
• Collaboration:
• Collaborate with Data Engineers, Analysts, and Business Intelligence teams to define data requirements, optimize queries, and improve reporting processes.
• Work with stakeholders to understand business needs and translate them into technical solutions.
• Performance Optimization:
• Identify performance bottlenecks in ETL processes and take proactive steps to optimize and improve processing times.
• Ensure ETL processes run efficiently, with minimal downtime and maximum throughput.
• Monitoring & Troubleshooting:
• Set up and maintain monitoring for ETL jobs to detect failures or performance issues.
• Troubleshoot and resolve ETL failures and performance issues promptly.
• Documentation & Reporting:
• Create and maintain comprehensive documentation for ETL processes, workflows, data sources, and transformations.
• Could you provide regular reports and status updates on ETL processes to management

Required Skills & Qualifications:

• Experience:
• 5+ years of hands-on experience designing, developing, and maintaining ETL pipelines in a complex, high-volume data environment.
• ETL Tools:
• Proficient in ETL tools such as Apache NiFi, Informatica PowerCenter, Talend, Microsoft SSIS, or cloud-based tools like AWS Glue, Google Dataflow, and Azure Data Factory.
• Databases & SQL:
• Strong SQL skills and experience working with relational databases (e.g., SQL Server, Oracle, MySQL, PostgreSQL).
• Ability to write optimized SQL queries, stored procedures, and functions to transform and load data efficiently.
• Data Warehousing Concepts:
• Familiarity with data warehousing concepts such as star schema, snowflake schema, and OLAP cubes.
• Experience working with large-scale data warehouses (e.g., Redshift, Snowflake, Google BigQuery, Teradata).
• Cloud Technologies:
• Experience with cloud platforms like AWS, Azure, or Google Cloud for data integration and management.
• Knowledge of cloud-native ETL tools, data lakes, and data pipelines.
• Scripting & Automation:
• Proficiency in scripting languages like Python, Bash, or Shell for automation and ETL process development.
• Data Quality & Monitoring:
• Knowledge of best practices in data quality assurance, monitoring, logging, and error handling in ETL pipelines.
• Version Control:
• Experience using Git or other version control systems for managing code and collaboration.
• Problem-Solving:
• Strong analytical and problem-solving skills with a focus on troubleshooting and resolving ETL issues.
• Communication:
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Preferred Skills:

• Experience with Big Data technologies like Hadoop, Spark, or Kafka for handling large datasets.
• Familiarity with Data Lake architectures and tools such as AWS S3, Azure Data Lake, or Google Cloud Storage.
• Knowledge of CI/CD pipelines and automation tools like Jenkins, Azure DevOps, or GitLab.
• Experience with Agile methodologies and tools (e.g., Jira, Confluence).