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Lead Data Engineer designing and building scalable real-time and batch data platforms for supply chain workflows using Python, SQL, PySpark, and container orchestration tools.
Build and maintain ETL/ELT pipelines using Informatica and Snowflake, develop data models, and manage metadata and data lineage with Informatica Data Catalog to support enterprise data governance and analytics.
Build and maintain data infrastructure—ETL pipelines, cloud data warehouse, and automated reporting—for a private credit investment firm in Gurugram, working with loan-level datasets and integrating servicer/financial data sources using SQL, Python, and cloud warehouses.
A Databricks Data Engineer role involving hands-on data engineering with Apache Spark, Databricks, Python/Scala, ETL pipelines, data warehousing, and cloud services (AWS/Azure) for large datasets.
Data Analyst/Data Engineer designing analytics architecture, managing databases, writing SQL queries, and automating Power BI reports for stakeholders.
Hands-on Solutions Architect role designing and building enterprise-grade data platforms on GCP/AWS using Snowflake, Databricks, BigQuery, Airflow, and Kafka to power AI/ML initiatives, with pre-sales responsibilities at a tech consultancy in Bangalore.
Lead Data Engineer overseeing enterprise-scale ETL and data modernization projects, architecting pipelines with Python, PySpark, Informatica, Databricks, Snowflake, ADF, and AWS Glue while mentoring a team of data engineers.
Databricks Data Engineering Architect defines and drives Databricks architecture and strategy, takes end-to-end ownership of Databricks solutions from design through implementation, and works with technologies like Databricks, Spark, Delta Lake, SQL, Python/PySpark, and Lakeflow.
GCP Data Engineer responsible for designing, building, and maintaining scalable data pipelines, data warehouses, and big data solutions on Google Cloud using Dataflow, BigQuery, Cloud Composer, and related GCP services.
Technical Lead driving the migration of Microsoft/Azure data platforms to Databricks, providing hands-on mentorship, architecture oversight, and pipeline development for the data engineering team.
Lead Data Engineer at IndusInd Bank in Mumbai, architecting and building a cloud-native Azure Databricks data platform with PySpark, leading a team of data engineers and analysts to deliver scalable lakehouse architectures and BI solutions.
Senior Data Engineer designing and maintaining real-time and batch data pipelines for SMC Global Securities' financial services and trading platforms, using SQL, Python, AWS (S3, Redshift, Athena, Glue, EMR, Lambda), Airflow, DBT, and Spark within Data Lakehouse architectures.
Data Engineer building and optimizing ETL/ELT pipelines with SQL and Python to create analytics-ready datasets for the Analytics team.
Design, build, and maintain the analytics data layer—pipelines (Airflow), warehouse (BigQuery), and ETL—on GCP, applying software engineering best practices to deliver BI solutions.
Senior Data Engineer building real-time data ingestion/processing pipelines and large-scale enterprise data solutions using PySpark, Python, Airflow, SQL, and AWS big data services.
Lead and hands-on build data & analytics solutions using Databricks, Informatica, and Tableau on AWS for Eisai's global pharmaceutical data platform, driving BI, AI, and data democratization.
Data Engineer designing, building, and supporting scalable data pipelines and integration solutions using Databricks, Spark/PySpark, SQL, and Azure data services for a major North American bank's tech hub in Hyderabad.
Design and build data pipelines and data models on Azure, Databricks, Snowflake, and Postgres to support AI/ML and computer-vision workflows for a digital transformation services company.
Senior Data Engineer designing and maintaining enterprise-scale data ingestion and integration solutions using Microsoft Fabric, Azure Data Services, SQL Server, and ETL/ELT pipelines.
Azure Data Engineer role at TCS Noida involving data ingestion, transformation, storage, warehousing, and modeling using Azure cloud services like Data Factory, Databricks, Synapse Analytics, and Python/PySpark.
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