Cloud Data Warehouses: Deep hands-on expertise in
Amazon Redshift and
Snowflake, including schema implementation, distribution/sort keys, clustering, query tuning, concurrency management, workload isolation, and cost optimization.
- Database Engineering & SQL: Advanced proficiency in SQL for complex transformations, analytical queries, window functions, stored procedures, and performance tuning across large-scale datasets.
- Data Integration & ETL/ELT: Design, develop, and maintain reliable ETL/ELT pipelines using AWS Glue, Apache Spark (PySpark), SQL, and Python to load and transform data from multiple sources.
- Change Data Capture & Streaming: Hands-on experience building CDC and streaming pipelines using AWS DMS, AWS MSK (Kafka), and Debezium for near–real-time data ingestion.
- AWS Data Ecosystem: Strong working knowledge of AWS S3, IAM, Lambda, Athena, Step Functions, and CloudWatch for data storage, orchestration, monitoring, and security.
- Data Modeling Implementation: Ability to implement and maintain ER models, dimensional models (star/snowflake schemas), and physical database designs optimized for analytics and reporting workloads.
- BI Data Enablement: Develop and optimize backend data models, views, and extracts to support Tableau and Power BI, ensuring performance, scalability, and data consistency.
- BI Performance & Security: Support Row-Level Security (RLS), column masking, governed datasets, and performance-optimized views/models for BI tools such as Tableau and Power BI.
- Automation & Scripting: Automate database operations, data refreshes, validations, and deployments using Python, Shell scripting, Tableau REST API, Power BI REST API, and scheduled workflows.
- Data Quality & Validation: Implement data quality checks, reconciliation logic, anomaly detection, and root-cause analysis using SQL, Python, and data profiling techniques.
- Performance & Cost Optimization: Monitor and tune query performance, storage usage, and compute costs using Snowflake query history, Redshift system tables, and AWS CloudWatch.
- Security & Compliance: Implement database security best practices including RBAC, IAM roles, encryption at rest and in transit, audit logging, and compliance with enterprise security standards.
- DevOps & CI/CD: Strong experience with Git, GitHub/GitLab, code reviews, and CI/CD pipelines using Jenkins, AWS CodePipeline, or equivalent tools for database and ETL deployments.
- Infrastructure as Code: Experience using Terraform and/or AWS CloudFormation to provision and manage database and data platform infrastructure.
- Operational Support & Reliability: Ownership of production data platforms, including monitoring, alerting, incident response, root-cause analysis, and performance troubleshooting.
- Agile Delivery: Experience working in agile teams using JIRA, Confluence, and sprint-based delivery models.
- Documentation & Standards: Maintain technical documentation, data dictionaries, operational runbooks, and database standards using tools such as Confluence, Lucidchart, or Draw.io.
- Collaboration & Mentorship: Ability to collaborate with data architects, BI teams, and application engineers, and mentor junior engineers on database and SQL best practices.
