Sai Kumar Sirangi
Senior Data Analyst / Data Engineer • s******************@gmail.com • 980****122
Professional Summary
Senior Data Analyst with 5+ years delivering analytics, data engineering and BI solutions across cloud and on-prem environments. Strong SQL and Python expertise with hands-on experience building ETL pipelines (Informatica, Airflow, Databricks), data models (dimensional and normalized), data quality frameworks and interactive dashboards (Tableau, Power BI). Experienced with Snowflake, Redshift, Teradata and AWS data services; skilled at optimizing queries and pipelines, enabling faster reporting and reliable ML-ready datasets. Collaborative communicator who partners with stakeholders, data architects and data scientists to translate business needs into production analytics.
Technical Skills
Programming Languages: Python,R,VBA
Frameworks and Libraries: pandas,NumPy,scikit-learn,matplotlib,seaborn
Databases: SQL,Snowflake,Amazon Redshift,Teradata,Oracle,SQL Server,MongoDB
Cloud and DevOps: AWS S3, Lambda, Glue, EMR, EC2,Jenkins,Docker,UNIX,Excel Pivot
Data and Analytics: Apache Spark,Databricks,Hadoop,Kafka,Tableau,Power BI,Looker,SAP BusinessObjects,Dimensional modeling,Star,Snowflake schemas,ERwin,Data quality and lineage
Tools and Methodologies: Git,JIRA
Skills: PySpark,SAS,PL
ETL & Orchestration: Informatica PowerCenter,Apache Airflow,Talend,SSIS
Work Experience
Unilever, TX
Senior Data Analyst/ Data engineer
Jun 2024 – Till date
Tech Stack: Python, PySpark, Databricks, Snowflake, Amazon S3, Redshift, Airflow, Informatica, Talend, Kafka, SQL, Tableau, UNIX
- Gathered and translated complex business requirements into analytics-ready data specifications; mapped source systems (Snowflake, Redshift, Oracle, MSSQL, APIs) to dimensional and normalized target models to support BI and ML use cases.
- Designed and implemented ETL and batch/near-real-time pipelines on Databricks and PySpark to ingest, transform and load data to Snowflake and S3, improving data availability for reporting.
- Built data validation, cleansing and reconciliation workflows (SQL, Python) to enforce data quality and lineage; implemented role-based access controls and encryption policies to meet compliance requirements.
- Developed Airflow/Databricks scheduling for automated data jobs and created Databricks scheduled jobs to push curated datasets to collaboration platforms, reducing manual intervention and operational errors.
- Implemented feature engineering and aggregation pipelines (PySpark, pandas, SQL) used by data science teams; accelerated model experimentation by delivering consistent training datasets.
- Optimized Spark jobs and Snowflake/Redshift SQL (query tuning, partitioning, clustering) and designed incremental ETL flows to reduce compute costs and improve run-times (reported improvements in ingestion and processing efficiency).
Albemarle CA
Data Analyst
Aug 2023 – May 2024
Tech Stack: Python, PySpark, Spark, AWS Lambda, AWS Glue, S3, Redshift, Hive, Tableau, Jenkins, Docker, SSIS, SSMS
- Built streaming and batch data ingestion pipelines using Python to read from the enterprise Streaming Data Platform and land curated datasets into the analytical cloud data warehouse for downstream analytics.
- Designed and delivered Tableau dashboards consolidating metrics from multiple sources; validated dashboard data using SSMS/SSIS and complex SQL queries to ensure reporting accuracy.
- Implemented serverless ETL workflows on AWS (Lambda, Glue, S3, Redshift) and tuned Hive/Spark batch jobs to process terabytes of structured and semi-structured data with improved stability.
- Established CI/CD patterns for data engineering using Git, Jenkins and Docker to standardize deployments and reduce release errors; automated data load processes and scheduling to accelerate delivery.
- Created and enforced data governance artifacts (data dictionaries, lineage, profiling) and collaborated with architects to define ETL metadata strategies supporting compliance and discoverability.
- Automated data workflows in Python/SQL/Spark to support ML model pipelines and reporting, decreasing manual effort by ~50% and improving pipeline reliability.
DCube Data Sciences, India
Data Analyst
Dec 2022 – Jul 2023
Tech Stack: SQL Server, SSMS, SSIS, T-SQL, PL, SQL, Power BI, Visual Studio
- Performed data ingestion and staging using SQL Server Import/Export and SSMS to load flat files (CSV, Excel, Parquet) and prepared cleansed datasets for analytics and reporting.
- Executed comprehensive data quality checks and data mapping to ensure accuracy and consistency across reporting feeds; documented transformations and staging rules for auditability.
- Developed and maintained PL/SQL and T-SQL routines to implement enhancements and resolve data issues, improving data processing stability for reporting consumers.
- Created SQL views and semantic layers to support Power BI dashboards, enabling self-service access to validated metrics for stakeholders.
- Collaborated with BI and analytics teams to troubleshoot ETL failures, tune import jobs and optimize data structures for faster query performance.
- Delivered repeatable staging patterns and data validation scripts that reduced end-to-end data preparation time and improved dashboard refresh reliability.
Netxcell Ltd., India
Software Engineer
Mar 2020 – Nov 2022
Tech Stack: C#, ASP.NET, SQL Server, Visual Studio, Crystal Reports, IIS, Oracle 8i, JavaScript
- Collected and analyzed functional requirements; authored SRS and designed N-tier application architectures using C# and ASP.NET to meet client specifications.
- Developed web UI components and reusable user controls (.ascx) and validation routines to improve UX consistency and accelerate feature delivery across modules.
- Implemented backend services and data access layers using stored procedures and SQL Server, optimizing queries for application responsiveness and data integrity.
- Built Crystal Reports and reporting interfaces, integrating them into the application for operational and management reporting requirements.
- Performed unit and integration testing, participated in deployment activities on IIS and provided production support to resolve defects and improve stability.
- Collaborated across teams to design document upload, multi-select controls and risk-question components that were reused across the application, reducing duplicate development.
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