kalyan pippera

• Designed and deployed predictive analytics dashboards in Tableau Desktop/Server, enabling workforce planners to reduce
reporting turnaround by 40% via real-time quick-filter views.
• Converted 50+ complex SQL queries to PySpark/Scala Spark transformations on Databricks; applied indexing, aggregation,
and materialised views, cutting query latency by ~35%.
• Built automated ETL workflows using Informatica IICS to migrate datasets across AWS, Azure, and GCP; enforced data quality
checks and validation rules ensuring 99%+ data accuracy.
• Scheduled and orchestrated batch pipelines using Informatica Workflow Manager and Control-M/Autosys, achieving zero
missed SLA across 200+ daily jobs.
• Integrated Power BI with REST APIs and Direct Query connectors; created DAX measures and Star Schema models to support
executive KPI reporting with sub-second refresh.
• Worked with Kafka and Apache NiFi to stream log files into Hadoop (HDFS/Hive), enabling near-real-time event processing for
workforce analytics use cases.
• Collaborated with cross-functional teams in Agile/Scrum sprints; served as internal QA tester, validating report accuracy before
production deployments.

• Architected scalable Azure Data Factory pipelines integrating GE PPA, REST APIs, and on-prem RDBMS sources; reduced data
ingestion time by 50% through parallel pipeline execution.
• Designed Snowflake data warehouses with role-based access controls, resource monitors, and query optimisation (clustering
keys, query pruning), improving warehouse performance by 30%.
• Modelled semantic layers using DAX and Star Schema in Power BI for OEE, downtime, and quality metric dashboards serving
manufacturing operations teams.
• Integrated MES and SCADA industrial data into Azure cloud via ADF and Python; built data models for production metrics,
enabling real-time operational efficiency tracking.
• Built and maintained AWS data pipelines using S3, EMR, Lambda, and AWS Glue (PySpark); created on-demand catalogued
tables from raw S3 files for downstream analytics.
• Implemented Informatica PowerCenter mappings for RDBMS, flat-file, and cloud sources; performed session-level and SQL
level performance tuning to improve load throughput.
• Developed shell scripts and Python automation for data transformation, API integration, and pipeline monitoring with
CloudWatch alerts.

• Assisted professors with Data Structures (Java) and Data Mining courses; mentored 30+ students through assignments,
worksheets, and lab sessions.
• Used Talend Data Fabric and IBM DataStage to demonstrate enterprise ETL patterns across Salesforce, SAP, and relational
database connectors.
• Performed dataset profiling and GDB_GP performance analysis; introduced students to classification and regression techniques
using real-world datasets.

• Developed ETL procedures ensuring data conformity and compliance with business rules; minimised data redundancy across
corporate-wide data warehouse solutions.
• Used Spark DataFrame API with Hive Context to accelerate analytical workloads; handed structured datasets to ML analytics
team with documented data lineage.
• Performed data profiling, anomaly detection, and trend correlation analysis; translated findings into actionable data-quality
improvement recommendations.