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Psoition: Lead Data Engineer
Locations: Fremont, CA (Onsite/ Need Only Local Candidates)
Duration: 12 Months
Note: Any Visa is Fine with Genuine Experience
Job Description:
Mandatory Skills: Azure Data Factory (ADF), Azure Databricks & PySpark, Azure Synapse, Azure SQL, Python, and Spark SQL
Accomplished Data Architect / Senior Data Engineer with 12 years of experience designing and modernizing enterprise data platforms across banking, healthcare and retail domains.
Architected scalable ETL/ELT pipelines using Python, PySpark, Databricks, AWS Glue and Azure Data Factory, supporting high-volume transactional and regulatory data processing.
Led enterprise-scale Data Architecture initiatives, defining logical and physical data models, governance standards and cloud-native platform blueprints across AWS and Azure environments.
Designed and implemented Medallion (Bronze/Silver/Gold) Lakehouse architectures using Delta Lake, S3, ADLS Gen2, Snowflake, Redshift and Synapse Analytics.
Engineered large-scale distributed processing workloads using Apache Spark, PySpark, Databricks, EMR, Hive and HDFS, processing billions of records for enterprise analytics.
Orchestrated complex data workflows using Apache Airflow, Databricks Workflows, AWS Step Functions and Azure Data Factory triggers, ensuring SLA-driven pipeline execution.
Strong hands-on experience in Advanced SQL, including complex joins, CTEs, window functions, stored procedures, indexing strategies, partitioning and execution plan optimization across Snowflake, PostgreSQL and Oracle.
Built real-time streaming architectures using Apache Kafka, AWS Kinesis, Azure Event Hub and Service Bus, supporting fraud detection, claims monitoring and operational telemetry.
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Psoition: Lead Data Engineer
Locations: Fremont, CA (Onsite/ Need Only Local Candidates)
Duration: 12 Months
Note: Any Visa is Fine with Genuine Experience
Job Description:
Mandatory Skills: Azure Data Factory (ADF), Azure Databricks & PySpark, Azure Synapse, Azure SQL, Python, and Spark SQL
Accomplished Data Architect / Senior Data Engineer with 12 years of experience designing and modernizing enterprise data platforms across banking, healthcare and retail domains.
Architected scalable ETL/ELT pipelines using Python, PySpark, Databricks, AWS Glue and Azure Data Factory, supporting high-volume transactional and regulatory data processing.
Led enterprise-scale Data Architecture initiatives, defining logical and physical data models, governance standards and cloud-native platform blueprints across AWS and Azure environments.
Designed and implemented Medallion (Bronze/Silver/Gold) Lakehouse architectures using Delta Lake, S3, ADLS Gen2, Snowflake, Redshift and Synapse Analytics.
Engineered large-scale distributed processing workloads using Apache Spark, PySpark, Databricks, EMR, Hive and HDFS, processing billions of records for enterprise analytics.
Orchestrated complex data workflows using Apache Airflow, Databricks Workflows, AWS Step Functions and Azure Data Factory triggers, ensuring SLA-driven pipeline execution.
Strong hands-on experience in Advanced SQL, including complex joins, CTEs, window functions, stored procedures, indexing strategies, partitioning and execution plan optimization across Snowflake, PostgreSQL and Oracle.
Built real-time streaming architectures using Apache Kafka, AWS Kinesis, Azure Event Hub and Service Bus, supporting fraud detection, claims monitoring and operational telemetry.
Phone:
E-mail: