Srikrishnan Shankar
Data Engineer @Legal & General
Signup · Get unlimited contacts
WORK HISTORY
Data Engineer @Legal & General
Hove, GB
Responsible for monitoring daily data batches in Wherescape Red and notifying the Business team via group emails.• Owned the end-to-end solution for the Group Protection business, developing data pipelines in Snowflake and designing dashboards in Power BI.• Facilitated the Broker Segmentation dashboard by creating a final reporting table in Snowflake using Wherescape objects and designing a Power BI dashboard to categorise intermediaries based on quotes and conversion rates, along with implementing RLS.• Enhanced the Discontinuance report in Power BI by creating a dashboard displaying the falsely discontinued records in the App.• Completed ad-hoc data requests in the SharePoint folder from the Business team, ensuring adherence to SDLC best practices.
EDUCATION
Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kancheepuram
Bachelor of Engineering - BE, Electrical and Electronics Engineering
ABOUT SRIKRISHNAN SHANKAR
Email: s••••••••@gmail.comData Engineer with 2+ years of experience building scalable data platforms and analytics solutions using modern cloud data stacks. I specialize in designing data lakehouse and data warehouse architectures using tools such as Snowflake, Google BigQuery, Databricks, SQL, and Python, with a focus on transforming raw data into reliable datasets for analytics and decision-making.In my current role at Legal & General, I work on modernizing legacy ETL workflows by migrating pipelines to dbt and Apache Airflow, enabling modular transformations, automated testing, and GitHub-driven CI/CD deployments. I have built and optimized Snowflake-based reporting pipelines using Kimball dimensional modeling, supporting multiple Tableau and Power BI dashboards used by business teams to monitor performance and outcomes.Previously at Onward Technologies, I worked on data integration and analytics projects using Google BigQuery and Airflow, developing pipelines and BI dashboards that helped teams analyze customer behavior, retention trends, and operational metrics.Beyond my professional work, I enjoy experimenting with modern data engineering patterns such as lakehouse architectures, Spark-based processing, and metadata-driven pipelines. I recently built a retail analytics warehouse project using Spark, Apache Iceberg, Airflow, and dbt to explore scalable data processing and analytics workflows.Key areas I work with- Data Engineering & ELT Pipelines (SQL, Python, Spark, Iceberg, dbt, Airflow, Wherescape Red, MSBI-SSIS)- Cloud Data Warehousing (Snowflake, BigQuery)- Databases (Microsoft SQL Server, Postgres)- Data Lakehouse Architectures (Medallion, Databricks, S3 / ADLS)- Data Modeling (Kimball Dimensional Modeling)- BI & Analytics (Tableau, Power BI, Looker Studio, Streamlit) Certifications:Acquired notable certifications from Coursera, Credly Badges, Udemy, and LinkedIn Learning.With a BE in Electrical Engineering and a robust portfolio of projects and certifications, I’m passionate about building reliable data platforms that empower analytics and business insights. Let’s connect and explore collaboration opportunities to turn data into powerful insights.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.