Data Engineer Power Bi

BALA KRISHNA GORANTLA

Fort Wayne, IN +1-781-***-**** ***********************@*****.*** LinkedIn PROFESSIONAL SUMMARY

Data Engineer with 4 years of experience designing scalable data platforms and ETL pipelines across AWS, Azure, and GCP. Skilled in PostgreSQL administration, high availability, disaster recovery, and performance optimization. Proficient in Airflow, dbt, Informatica, AWS Glue, Python, and SQL for real-time analytics. Experienced in delivering BI solutions with Redshift, BigQuery, Power BI, and Tableau, improving reporting speed and decision- making. Certified in IBM Data Engineering, Google Cloud Data Engineer, and dbt. TECHNICAL SKILLS

Databases & Data Warehousing: PostgreSQL, MySQL, SQL Server, Snowflake, Google BigQuery, Amazon Redshift. Data Engineering & ETL Pipelines: Apache Airflow, dbt, Apache Kafka, Apache Spark, AWS Glue, Talend, Informatica, SSIS. Cloud Platforms: AWS (RDS, S3, Glue, EMR, Lambda, Redshift), Azure (Data Factory, Synapse, Databricks), Google Cloud Platform (BigQuery, Dataflow, Pub/Sub).

Programming & Scripting: Python, SQL, Shell Scripting, PL/pgSQL. DataOps, CI/CD & Monitoring: Git, Jenkins, Docker, Kubernetes, Terraform, Ansible, Prometheus, Grafana, pgBadger, pgPool, PgBouncer. Business Intelligence & Analytics: Power BI, Tableau, Looker, Metabase. Operating Systems: Linux (RedHat, CentOS, Ubuntu). Collaboration & Workflow Tools: Jira, Confluence.

PROFESSIONAL EXPERIENCE

Data Platform Engineer Jan 2022 – Aug 2023

HCL Technologies Bengaluru, India

• Engineered ETL pipelines with Airflow and Informatica to integrate subscriber, billing, and usage data into PostgreSQL and AWS S3, reducing manual processing by 55% and accelerating analytics readiness.

• Configured and optimized PostgreSQL 12 on Linux with automated backups, user roles, and encryption, maintaining 99.9% availability and compliance.

• Designed and executed disaster recovery and PITR strategies, achieving RPO under 10 minutes and ensuring uninterrupted telecom analytics operations.

• Optimized large-scale tables using partitioning, indexing, and query tuning, boosting query performance by 50% and lowering resource consumption by 20%.

• Automated data archival workflows to AWS S3 and Glacier, cutting on-premise storage costs by 30% while ensuring rapid BI reporting retrieval.

• Delivered analytics-ready datasets for Power BI dashboards, enabling near real-time KPI monitoring and reducing reporting turnaround from 48 hours to 4 hours.

• Implemented CI/CD pipelines with Jenkins and Git for ETL jobs and schema changes, reducing deployment errors by 70% and cutting release cycles by half while collaborating on scalable data warehouse design. Data Engineer Feb 2020 – Dec 2021

DBA CYBUS SOLUTIONS Hyderabad, India

• Developed and orchestrated ETL pipelines with Apache Airflow and Python to ingest IoT, API, and batch energy data into PostgreSQL RDS and Redshift, reducing data availability time by 94%.

• Transformed raw data into analytics-ready datasets using dbt models and SQL workflows, standardizing KPIs and cutting manual preprocessing by 60% while improving downstream query performance.

• Administered PostgreSQL clusters on AWS RDS with Multi-AZ deployment, read replicas, and automated snapshots, ensuring 99.99% uptime and seamless analytics access.

• Designed and validated DR pipelines with streaming replication, executing switchover drills to achieve RPO under 5 minutes and RTO under 30 minutes for mission-critical energy workloads.

• Optimized database performance through index restructuring, table partitioning, and automated VACUUM operations, lowering query latency by 35% and CPU utilization by 20%.

• Built monitoring dashboards in Prometheus and Grafana to track replication lag, bottlenecks, and cluster health, reducing issue detection time by 66%.

• Automated schema migrations, incremental data loads, and dbt deployments via Jenkins and GitHub Actions, cutting release time by 50% and minimizing deployment errors by 70% while enabling curated datasets for Tableau reporting. PROJECTS

Energy Data Lake for Real-Time Analytics

• Integrated IoT meters and ERP data into PostgreSQL and Redshift, creating a scalable data lake for real-time analytics.

• Automated batch and streaming pipelines using Airflow and AWS Glue, ensuring consistent data ingestion and transformation.

• Standardized metrics with dbt and developed Tableau dashboards, enabling monitoring of energy usage trends and peak demand forecasting.

Telecom Customer 360 Data Warehouse

• Consolidated legacy subscriber, billing, and usage data into a centralized PostgreSQL warehouse, enabling consistent analytics across departments.

• Built ETL workflows with Informatica to transform multi-source data into structured AWS S3 schemas, improving reliability.

• Developed secure access layers with role-based permissions and delivered Power BI dashboards for churn analysis, revenue forecasting, and network performance monitoring.

EDUCATION

Master of Science in Information Systems Aug 2023 - Apr 2025 Indiana Institute of Technology Fort Wayne, IN

Bachelor of Technology in Computer Science Apr 2016 – Apr 2020 Koneru Lakshmaiah College of Engineering Hyderabad, India CERTIFICATIONS

• SQL Certification - Hacker Rank

• IBM Data Engineering Professional Certificate - Coursera

• Google Data Analytics Professional Certificate - Coursera

• Google Cloud Professional Data Engineer - Coursera

• Data Engineering Foundations - LinkedIn Learning

• Building Data Pipelines with Python - LinkedIn Learning

Contact this candidate