Divyasri Nalimela

Senior Data Engineer @ Fidelity Investments

About

I am an experienced professional and a graduate with a focus on data-driven analytics. Well-acquainted with Pipelines, Data structures, Data management, and processing systems. Proficient knowledge of statistics, mathematics, and analytics. Excellent understanding of business operations. Strong desire to move forward, face new challenges, and expand my skill set. I’d strategically break down my core skillsets as follows; Languages: Python, R, Linux Databases: MySQL, SQL Server, Oracle, Amazon Redshift, NoSQL Big Data Technologies: Hadoop, HDFS, Hive, Sqoop, Oozie, Apache Spark, Airflow Cloud Technologies: AWS S3, EMR, EC2, Glue, Lambda, Quicksight, Google Cloud Storage, Cloud SQL, Big Query, Data Proc, Pub/Sub Visualization & Others: Tableau, Power BI, IBM Cognos Analytics, Excel, Word, Docker, JIRA To that effect, I am actively searching for Data Engineer/ Data Scientist/Data Analyst Full-time positions.

Country

United States

City

Greater Boston

Industry

Higher Education

Skill

Business Requirements, Data Models, Apache Spark, Extract, Transform, Load (ETL), IBM Cognos Analytics, ETL Tools, PySpark, NoSQL, EER, Unified Modeling Language (UML), Hadoop, Python (Programming Language), R (Programming Language), MySQL, Tableau, Amazon Web Services (AWS), SQL, Microsoft Excel, Data Warehousing, Business Intelligence (BI)

Experience

Senior Data Engineer

Fidelity Investments

2026-1 - Present · 9 mos

Designed and delivered enterprise-scale data pipelines and batch processing frameworks supporting critical financial data workflows — built for throughput, consistency, and operational resilience. Architected solutions leveraging Spring Batch and AWS Batch for large-scale job execution, with infrastructure across S3, EC2, Lambda, IAM, and CloudWatch for observability and control. Containerized workloads using Docker and managed job scheduling through Control-M. Core development in Java, with CI/CD delivery via Jenkins and GitHub. Worked across the full data stack — Snowflake for cloud analytics, Oracle SQL for enterprise data, and Power BI for downstream reporting — translating complex data into reliable, business-ready pipelines.

AWS Data Engineer

Fannie Mae

2023-2 - 2025-12 · 2 yrs 11 mos

Virginia, United States

Developer IV | Data Engineer @ Fannie Mae Designing and owning data infrastructure that keeps critical systems running at scale — end-to-end pipelines spanning ingestion, transformation, and downstream analytics, built for the reliability and performance enterprises depend on. Deep hands-on experience across the full AWS stack (Lambda, Step Functions, S3, EC2, EventBridge, IAM), including high-volume event-driven workloads through SNS/SQS. Workflow orchestration with Airflow and AutoSys, core development in Python and SQL, Oracle environments via Toad, and production delivery through Jenkins, UCD, and Bitbucket. Drawn to problems where distributed systems, data quality, and scale intersect — and focused on building solutions that hold up under pressure.

Graduate Teaching Assistant

Northeastern University College of Engineering

2022-9 - 2022-12 · 4 mos

Boston, Massachusetts, United States

Data Management for Analytics

Data Engineer

NTT DATA North America

2019 - 2021 · 2 yrs

United States

Data Engineer/ Data Analyst

Wipro Limited

2016 - 2019 · 3 yrs

United States

Education

Northeastern University

Data Analytics Engineering

2021 - 2022-12 · 2 yrs

Relevant Courses: Computation and Visualization, Data Management for Analytics, Engineering Probability & Statistics, Data Mining in Engineering, Big Data Architecture and Governance, Operations Research, Machine Learning, and AWS Cloud Architecting.