Data Engineer

Data EngineerData Pipelines - Design, develop, and maintain data pipelines for efficient data processing and integration for real-time and batch-processing. Implement and optimize ETL processes to extract, load, transform and integrate data from various sources. Enhance data flows and storage solutions for improved performanceData Warehousing - Design and implement data warehouse structures. Ensure data quality and consistency within the data warehouse. Apply data modeling techniques for efficient data storage and retrievalData Governance, Quality & Compliance - Implement data governance policies and procedures. Implement data quality frameworks, standards and documentation. Ensure compliance with relevant data regulations and standardsSecurity & Access Management - Implement data security measures and access controls. Maintain data protection protocolsPerformance Optimization and Troubleshooting - Analyze and optimize system performance for large-scale data operations. Troubleshoot data issues and implement robust solutionsTesting & Automation – Write unit test cases, validate the data integrity & consistency requirements, adopt automated data pipelines using GitLab, Github, CICD toolsCode Deployment & Release Management - Adopt release management processes to promote code deployment to various environments including production, disaster recovery, and support activitiesCross-Functional Collaboration - Collaborate with data scientists, analysts, and other teams to understand and meet data requirements. Participate in cross-functional projects to support data-driven initiativesTechnical/Business Skills: Hands-on experience in building robust metadata-driven, automated data pipeline solutions leveraging modern cloud-based data technologies, tools for large data platforms. Hands-on experience leveraging data security, governance methodologies meeting data compliance requirements. Experience building automated ELT data pipelines, snowpipe frameworks leveraging Qlik Replicate, DBT Cloud, snowflake with CICD. Hands-on experience building data integrity solutions across multiple data sources and targets like SQL Server, Oracle, Mainframe-DB2, files, Snowflake. Experience working with various structured & semi-structured data files - CSV, fixed width, JSON, XML, Excel, and mainframe VSAM. Experience using S3, Lambda, SQS, SNS, Glue, RDS AWS services. Proficiency in Python, Pyspark, advanced SQL for ingestion frameworks and automation. Hands-on data orchestration experience using DBT cloud, Astronomer Airflow. Experience in implementing logging, monitoring, alerting, observability, performance tuning techniques. Implement and maintain sensitive data protection strategies – tokenization, snowflake data masking policies, dynamic & conditional masking, and role based masking rules. Strong experience designing, implementing RBAC, data access controls, adopting governance standards across Snowflake and supporting systems. Strong experience in adopting release management guidelines, code deployment to various environments, implementing disaster recovery strategies, leading production activities. Experience implementing schema drift detection and schema evolution patterns. Must have one or more certifications in the relevant technology fields. Nice to have Financial banking experience.