Azure Data Engineer-Hybrid Role

Role: Azure Data Tech Lead

Location: Alpharetta, GA (Hybrid)

Duration: 12+ Months

Must Have:

• Azure Databricks
• SQL
• Spark
• Azure
• Databricks
• ADLS
• Spark (Python)
• SQL
• ETL
• Delta Lake
• PostgreSQL
• Data Architecture
• Batch & Real-time Processing
• Data Modelling

Overview:

We are 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.

Responsibilities:

• Architect, design, and implement scalable data platforms and pipelines on Azure and Databricks.
• Build and optimize data ingestion, transformation, and processing workflows across batch and real-time data streams.
• Work extensively with ADLS, Delta Lake, and Spark (Python) for large-scale data engineering.
• Lead the development of complex ETL/ELT pipelines, ensuring high quality, reliability, and performance.
• Design and implement data models, including conceptual, logical, and physical models for analytics and operational workloads.
• Work with relational and lakehouse systems including PostgreSQL and Delta Lake.
• Define and enforce best practices in data governance, data quality, security, and architecture.
• Collaborate with architects, data scientists, analysts, and business teams to translate requirements into technical solutions.
• Troubleshoot production issues, optimize performance, and support continuous improvement of the data platform.
• Mentor junior engineers and contribute to building engineering standards and reusable components.

Requirements:

• 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.
• Ability to design end-to-end solutions, evaluate trade-offs, and recommend best-fit architectures.
• Strong analytical, problem-solving, and communication skills.
• Ability to collaborate with cross-functional teams and lead technical discussions.

Early response is appreciated....
 
In compliance with the salary transparency law, the expected pay range for this role is $60-62. Actual compensation depends on experience and interview evaluation.
 

Thanks

Piyush Verma Lead Technical Recruiter | Empower Professionals

|Official Phone: x 350

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