Data Engineer Real-Time

SRINIVAS VENGALA

+1-940-***-**** ******************@*****.***

www.linkedin.com/in/srinivas-vengala-200842171

Versatile and results-oriented Data Engineer with over 3+ years of experience in designing, developing, and maintaining scalable data pipelines across healthcare, financial, and enterprise domains. Proficient in building cloud-native data architectures using AWS and GCP, with hands-on expertise in real-time data streaming (Kafka, Kinesis), ETL orchestration (Airflow, AWS Glue), and big data processing (Spark, Databricks, Hadoop). Strong track record in optimizing SQL and NoSQL performance, enabling cost-effective, high-availability analytics solutions using Redshift, Snowflake, and BigQuery. Adept at implementing data governance, lineage tracking, security protocols (HIPAA, PII masking), and automated quality checks. Known for driving data platform modernization through legacy system migration, workflow automation, and collaborative solution delivery across DevOps, BI, and business teams.

PROFESSIONAL EXPERIENCE:

MOLINA HEALTHCARE IRVING, TX FEB 2024 – PRESENT

DATA ENGINEER

RESPONSIBILITIES:

Designed scalable ETL workflows using AWS Glue and Databricks, reducing data ingestion time by 30%.

Implemented BigQuery partitioning and clustering for optimized query performance (40% improvement).

Built real-time streaming pipelines using AWS Kinesis and Firehose to minimize report latency.

Developed automated validation scripts for data monitoring, improving reliability and accuracy.

Integrated data from various healthcare systems (EHR, claims, pharmacy) into centralized data lake, enabling unified reporting.

Created Python-based data quality frameworks to perform schema validations and null checks on incoming datasets.

Collaborated with BI teams to define KPIs and deliver curated data marts for Tableau and Power BI dashboards.

Applied encryption and masking techniques to handle PHI/PII data in compliance with HIPAA and HITRUST standards.

Optimized AWS Glue job execution by tuning Spark configurations and leveraging dynamic frames.

Configured Airflow DAGs to orchestrate ETL workflows and ensure SLA compliance across healthcare pipelines.

Conducted root cause analysis of latency spikes and implemented proactive monitoring with CloudWatch and Datadog.

Partnered with DevOps to containerize ETL components using Docker and deploy on AWS Fargate for better scalability.

Assisted in cost analysis and budget optimization by monitoring AWS resource usage and identifying underutilized services.

Provided knowledge-sharing sessions to cross-functional teams on using AWS native analytics tools effectively.

TATA CONSULTANCY SERVICES HYDERABAD, INDIA. NOV 2021 – DEC 2022

SYSTEM ENGINEER

RESPONSIBILITIES:

Engineered and maintained cloud-based data pipelines, improving data transformation efficiency by 30%.

Automated cloud operations using AWS Lambda & Step Functions, reducing manual intervention by 40%.

Optimized SQL queries, improving data retrieval speed by 35% in reporting dashboards.

Developed scalable ETL frameworks processing millions of transactions daily, ensuring 99.9% uptime.

Mentored and trained 20+ engineers on data engineering best practices, enhancing team efficiency.

Conducted source-system and transformation analysis, ensuring data integrity and compliance with business needs.

Implemented change data capture (CDC) logic using AWS DMS for near real-time synchronization across distributed systems.

Developed data lineage and auditing scripts to track transformation logic and ensure transparency in reporting.

Built automated data archival processes to manage historical data in S3 and reduce storage costs.

Integrated role-based access controls (RBAC) for secure access to ETL logs and dashboards.

Worked with DevOps to deploy ETL applications via Jenkins and Terraform, improving deployment consistency.

Partnered with business analysts to define data requirements and deliver analytical models for fraud detection.

Created monitoring dashboards in QuickSight to provide stakeholders with pipeline performance metrics.

Developed version-controlled, parameterized ETL templates, accelerating onboarding of new data sources.

Assisted in migrating on-prem Oracle workloads to Amazon Redshift, reducing license and operational overhead.

SCION INFOSCRIBE SERVICES PRIVATE LIMITED HYDERABAD, INDIA. FEB 2021 – NOV 2021

DATA ENGINEER

RESPONSIBILITIES:

Developed and automated ETL pipelines, processing over 1M+ records daily with 99.8% accuracy.

Migrated 5+ legacy systems to cloud platforms, reducing operational costs by 25% and improving scalability.

Built data transfer frameworks using Apache NiFi, optimizing large-scale data movement efficiency.

Designed and deployed data models in Snowflake & Redshift, optimizing analytical queries by 40%.

Created real-time dashboards in Power BI & Tableau, enabling actionable insights for business teams.

Integrated structured and semi-structured data sources (CSV, JSON, XML) into cloud data lakes for unified access.

Performed data profiling and cleansing using Python and SQL to ensure high-quality datasets for analytics teams.

Collaborated with QA and data analysts to implement automated data validation and reconciliation checks.

Developed metadata-driven ETL processes to support dynamic pipeline configuration and scaling.

Documented data lineage and transformation logic, improving maintainability and stakeholder transparency.

Designed automated alerting systems using AWS SNS and CloudWatch for failed jobs or data anomalies.

Partnered with cross-functional teams to gather data requirements and deliver business-critical insights.

Conducted root cause analysis for data pipeline failures and implemented permanent remediation strategies.

Ensured compliance with data governance standards by implementing secure storage and masking for PII data.

Created reusable components for ingestion and transformation, reducing development time for new data sources.

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