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  Data Engineer with 7+ years building production-grade data platforms and Lakehouse architectures across banking, healthcare, and telecom, leading work end to end from requirements and design through release validation and production support.
  Implemented Azure and AWS Lakehouse platforms end to end using Azure Databricks, Delta Live Tables, Unity Catalog, Auto Loader, and Medallion Architecture, establishing reusable pipeline and data modeling standards teams could build on confidently.
  Built multi-cloud ETL and ELT pipelines across Azure (Data Factory, Databricks, ADLS Gen2, Synapse Analytics, Microsoft Fabric), AWS (Glue, EMR, Lambda, Step Functions, Redshift, Athena), and GCP (BigQuery), handling CDC, schema evolution, late-arriving data, and backfill strategies.
  Developed Python and Scala backend services with REST APIs, GraphQL, OAuth2/JWT authentication, PostgreSQL state management, and Redis caching, owning production observability through Datadog monitoring, incident response, and postmortems.
  Orchestrated complex workflows using Apache Airflow, Databricks Workflows, and AWS Step Functions, built governed ELT models using dbt and Snowflake, and partnered with analytics and business teams to define data contracts, data catalogs, and reduce recurring ad hoc requests.
  Established data quality and governance programs using Delta Live Tables Expectations, Great Expectations, and Soda across HIPAA, SOX, and GDPR-regulated pipelines for audit readiness, data lineage, and regulatory compliance.
  Translated ambiguous business requirements into well-scoped engineering deliverables, communicated progress clearly to finance, compliance, and clinical stakeholders, and managed competing priorities effectively across Agile sprint cycles.
  Set pipeline, data modeling, and coding standards in PySpark, Scala, Python, and SQL, mentored engineers at different levels, conducted code reviews, and drove CI/CD through GitHub Actions, Azure DevOps, and Terraform.


Experienced Data professional with over 4+ years of expertise in data engineering and analysis. Skilled in developing architecture solutions, constructing ETL pipelines, and providing technical leadership. Proficient in data modeling and adept at leveraging various tools and technologies. Seeking roles as a Data Engineer to design robust data infrastructure or as a Data Analyst to analyze and derive insights from complex datasets.

Results-driven Data Engineer with over 2 years of experience in building automated ETL pipelines, cloud-based data solutions, and enterprise-scale reporting systems. Proficient in Python, SQL, Spark, and Azure / AWS cloud services. Skilled in data modeling, big data tools, and implementing secure and optimized data lake / warehouse solutions. Adept at working with business stakeholders to deliver scalable and reliable analytics infrastructure for decision-making.

Experienced Data Engineer with a decade of expertise in designing and optimizing data pipelines across AWS, GCP, and Azure platforms. Successfully implemented large-scale data processing using Hadoop (HDFS, MapReduce), Spark, and Databricks, resulting in enhanced speed and reliability of analytics workflows. Developed efficient ETL frameworks utilizing AWS Glue, Talend, and DataStage to streamline data ingestion and transformation processes. Architected scalable solutions on AWS EC2 with Autoscaling, Azure Synapse, and GCP BigQuery to support high-volume data and complex queries. Proficiently managed real-time data streaming through Kafka, Pub/Sub, and Azure Event Hubs to ensure low-latency analytics and rapid insights. Demonstrated expertise in optimizing database performance in Snowflake, PostgreSQL, MySQL, and DB2, leading to improved query execution and resource utilization. Leveraged Tableau, Power BI, and SSRS as BI and reporting tools to deliver actionable insights through interactive dashboards. Configured robust security measures with IAM Security, VPC Configuration, and best practices to safeguard data against breaches. Automated workflows using shell scripting, Python, and Unix to reduce manual interventions and accelerate deployments. Proven track record of adopting Agile methodologies and Microservices principles to effectively coordinate cross-functional teams and drive continuous integration for data-driven projects. Proactive and goal-oriented professional with excellent time management and problem-solving skills. Known for reliability and adaptability, with swift capacity to learn and apply new skills. Committed to leveraging these qualities to drive team success and contribute to organizational growth.

Results-driven Data Engineer with 8+ years of expertise building enterprise-scale data solutions for financial services organizations. Specialized in designing robust ETL pipelines using Ab Initio, AWS/Azure cloud platforms, and modern visualization frameworks (Tableau, Angular). Proven track record leading technical teams, optimizing data workflows, and implementing risk controls for regulatory compliance. Expert in Spark, Python, SQL, Snowflake, and Databricks with demonstrated ability to reduce costs while improving performance.

Praneeth Abhiram Komarneni

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Data Engineer

Technical Support Associate

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Bachelor of Science - Computer Science

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Data Engineer

Technical Support Associate

Bachelor of Science - Computer Science

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