Data Analytics
PythonJob Description: Data Engineer
Location: Remote
Experience Required: 6 to 12 years in Data Engineering
Employment Type: [Full-time]
Notice: Looking for candidates, Who can join immediately or 15days Max
About the Role:
We are looking for a highly skilled Data Engineer with extensive experience in Python, Databricks, and Azure services. The ideal candidate will have a strong background in building and optimizing ETL processes, managing large-scale data infrastructures, and implementing data transformation and modeling tasks.
Key Responsibilities:
ETL Development:
Use Python as an ETL tool to read data from various sources, perform data type transformations, handle errors, implement logging mechanisms, and load data into Databricks-managed delta tables.
Develop robust data pipelines to support analytics and reporting needs.
Data Transformation & Optimization:
Perform data transformations and evaluations within Databricks.
Work on optimizing data workflows for performance and scalability.
Azure Expertise:
Implement and manage Azure services, including Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
Coding & Development:
Utilize Python for complex tasks involving classes, objects, methods, dictionaries, loops, packages, wheel files, and database connectivity.
Write scalable and maintainable code to manage streaming and batch data processing.
Cloud & Infrastructure Management:
Leverage Spark, Scala, and cloud-based solutions to design and maintain large-scale data infrastructures.
Work with cloud data warehouses, data lakes, and storage formats.
Project Leadership:
Lead data engineering projects and collaborate with cross-functional teams to deliver solutions on time.
Required Skills & Qualifications:
Technical Proficiency:
- Expertise in Python for ETL and data pipeline development.
- Strong experience with Databricks and Apache Spark.
- Proven skills in handling Azure services, including Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
Experience & Knowledge:
- Minimum 6+ years of experience in data engineering.
- Solid understanding of data modeling, ETL processes, and optimizing data pipelines.
- Familiarity with Unix shell scripting and scheduling tools.
Other Skills:
- Knowledge of cloud warehouses and storage formats.
- Experience in handling large-scale data infrastructures and streaming data.
Preferred Qualifications:
- Proven experience with Spark and Scala for big data processing.
- Prior experience in leading or mentoring data engineering teams.
- Hands-on experience with end-to-end project lifecycle in data engineering.
What We Offer:
- Opportunity to work on challenging and impactful data projects.
- A collaborative and innovative work environment.
- Competitive compensation and benefits.
How to Apply:
Shubham Vishwakarma
Full Stack Developer - Averlon
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon