Saransh Inc
Senior/Lead Data Engineer (Azure Databricks) - Fulltime Role
Saransh Inc, Alpharetta, Georgia, United States, 30239
Senior/Lead Data Engineer (Azure Databricks)
Location:
Alpharetta, GA (Onsite)
Job Type:
Full Time
Responsibilities
Looking for an experienced Senior/Lead Data Engineer with 8+ years of expertise in designing and delivering scalable, high‑performing data solutions on the Azure ecosystem.
The ideal candidate will have deep hands‑on experience with Databricks, Spark, modern data lakehouse architectures, data modelling, and both batch and real‑time data processing.
You will be responsible for driving end‑to‑end data engineering initiatives, influencing architectural decisions, and ensuring robust, high‑quality data pipelines.
Experience And Qualifications (Required)
8+ years of hands‑on data engineering experience in enterprise environments.
Strong expertise in Azure services, especially Azure Databricks, Functions, and Azure Data Factory (preferred).
Advanced proficiency in Apache Spark with Python (PySpark).
Strong command over SQL, query optimization, and performance tuning.
Deep understanding of ETL/ELT methodologies, data pipelines, and scheduling/orchestration.
Hands‑on experience with Delta Lake (ACID transactions, optimization, schema evolution).
Strong experience in data modelling (normalized, dimensional, lakehouse modelling).
Experience in both batch processing and real‑time/streaming data (Kafka, Event Hub, or similar).
Solid understanding of data architecture principles, distributed systems, and cloud‑native design patterns.
Preferred
Experience with CI/CD tools such as Azure DevOps and Git.
Familiarity with IaC tools (Terraform, ARM).
Exposure to data governance and cataloging tools (Azure Purview).
Experience supporting machine learning or BI workloads on Databricks.
Note Visa Independent candidates are highly preferred.
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Alpharetta, GA (Onsite)
Job Type:
Full Time
Responsibilities
Looking for an experienced Senior/Lead Data Engineer with 8+ years of expertise in designing and delivering scalable, high‑performing data solutions on the Azure ecosystem.
The ideal candidate will have deep hands‑on experience with Databricks, Spark, modern data lakehouse architectures, data modelling, and both batch and real‑time data processing.
You will be responsible for driving end‑to‑end data engineering initiatives, influencing architectural decisions, and ensuring robust, high‑quality data pipelines.
Experience And Qualifications (Required)
8+ years of hands‑on data engineering experience in enterprise environments.
Strong expertise in Azure services, especially Azure Databricks, Functions, and Azure Data Factory (preferred).
Advanced proficiency in Apache Spark with Python (PySpark).
Strong command over SQL, query optimization, and performance tuning.
Deep understanding of ETL/ELT methodologies, data pipelines, and scheduling/orchestration.
Hands‑on experience with Delta Lake (ACID transactions, optimization, schema evolution).
Strong experience in data modelling (normalized, dimensional, lakehouse modelling).
Experience in both batch processing and real‑time/streaming data (Kafka, Event Hub, or similar).
Solid understanding of data architecture principles, distributed systems, and cloud‑native design patterns.
Preferred
Experience with CI/CD tools such as Azure DevOps and Git.
Familiarity with IaC tools (Terraform, ARM).
Exposure to data governance and cataloging tools (Azure Purview).
Experience supporting machine learning or BI workloads on Databricks.
Note Visa Independent candidates are highly preferred.
#J-18808-Ljbffr