Srikanth Anakali

Azure & Snowflake Data Engineering Professional with nearly 5 years of experience designing and delivering cloud-native data platforms, specializing in Azure Data Ecosystem, ETL/ELT pipeline engineering, and modern Data Lakehouse architectures across healthcare and telecom domains. Expertise in Azure Data Factory (ADF), ADLS, Databricks, and Delta Lake, building scalable data ingestion, transformation, and orchestration frameworks supporting structured and semi-structured data processing and near real-time analytics. Advanced proficiency in SQL and PySpark, enabling high-performance data transformation, large-scale data processing, and query optimization across distributed data environments.

Hands-on experience in Snowflake data warehousing, including data modeling, performance tuning, schema design, and cloud integration, supporting high-volume analytical workloads. Proven track record in developing and managing end-to-end ETL/ELT pipelines, integrating data from SQL Server, APIs, flat files, and enterprise systems, ensuring data quality, consistency, and reliability. Exposure to Data Lake and Lakehouse architecture design, implementing secure, scalable, and cost-optimized data solutions aligned with enterprise data strategies.

Strong background in hybrid and legacy data environments, leveraging Informatica PowerCenter and Teradata for data integration, migration, and modernization initiatives. Expertise in CI/CD pipelines, workflow orchestration, and job scheduling using tools such as Control-M, Git, and Azure-based pipeline frameworks, driving automation and deployment efficiency.

Experience delivering near real-time data solutions and supporting production environments with performance tuning, RCA, and continuous optimization of data pipelines. Leadership exposure through coordinating and guiding a team of 5 members in Azure data engineering projects, ensuring timely execution and alignment with delivery objectives.

Certified Microsoft Azure Data

Engineer (DP-203) and Snowflake SnowPro Core, with strong alignment to modern data engineering best practices, cloud optimization, and scalable architecture design.

Senior Systems Engineer at Infosys Limited (2023-09 – Present)

Client: CVS Health | Azure Data Engineer

• Built & orchestrated Azure data pipelines integrating SQL Server, APIs, and flat files into ADLS. Designed scalable, secure & cost-efficient data lake architectures.
• Developed Databricks workflows with Delta Lake, improving processing performance. Created PySpark/SQL transformations to enhance data quality and consistency.
• Implemented schema drift handling, audit controls, and error logging to improve reliability. Delivered near real-time pipelines supporting 100+ users. Automated scheduling via Control-M and improved performance through tuning and support.

Systems Engineer – Data Engineer at Infosys Limited (2021-09 – 2023-09)

Client: T-Mobile | DevOps IT

• Developed and maintained ETL pipelines for telecom operations. Engineered 30+ tables and managed 600+ ETL tables. Performed RCA and resolved recurring ETL failures. Optimized workflows to improve performance.
• Mentored juniors and supported Agile delivery. Assisted in data migration and legacy ETL decommissioning.

B.Tech. in CSE – KSRM College of Engineering (2015 – 2019)