Sandeep Edukulla

Over 8 years of experience in ETL processes, data integration, data analytics, and business intelligence, with a proven history of leading end-to-end project executions using Agile and Scrum methodologies. Effective communicator with strong collaboration and problem-solving skills, capable of translating complex technical requirements into actionable data-driven solutions for stakeholders. Extensive experience in ETL development using Apache Airflow, dbt, Snowpipe, Informatica, SSIS, and Apache Spark with Databricks, with proficiency in Hadoop ecosystem technologies Hive, MapReduce, HDFS, and BigQuery for large-scale data processing and distributed computing. Led dbt projects by designing models in intermediate and marts folders, defining access as public for referencing across all projects, implemented snapshots, seeds, constraints, and custom macros, and leveraged packages like audit_helper and dbt-jobs-as-code to ensure data validation and automated transformation workflows. Skilled in database architecture, data modeling, query optimization, and indexing, with expertise in handling diverse data formats (CSV, JSON, Parquet), integrating NoSQL databases, and enforcing data quality checks and constraints to ensure data integrity and support strong data governance. Experienced in relational databases with expertise in schema design and implementation of SCD Type 1 and Type 2 data models, tables, stored procedures, views, and datasets using SQL. Proficient in dbt features YAML configurations, snapshots, macros, and built-in testing to support historical tracking, documentation standards, and strong data governance. Proficient in Python for developing custom data transformation scripts, integrating with orchestration tools by building Apache Airflow DAGs, and connecting to REST APIs to support both batch and real-time data processing. Hands-on experience with GCP, AWS, and Azure, managing real-time data pipelines using Kafka and Flink. Skilled in building CI/CD workflows with GitHub Actions and orchestrating containers using Kubernetes. Applied performance tuning and cost optimization techniques across cloud platforms to ensure efficient, scalable, and reliable data processing. Adept at working across diverse data domains including supply chain, finance, and marketing, with experience in real-time lead ingestion, KPI modeling, and the use of BI tools such as Tableau, Power BI, Business Objects, and SSRS for interactive reporting and insight delivery. Collaborated with ML engineers and data scientists to integrate APIs and utilize predictive models supporting AI/ML use cases. Quick learner with awareness of evolving trends in Generative AI and prompt engineering.