SCALA Data Engineer
1 week ago
Job Title: Data Engineer (SCALA)
Location: Pune, India
Experience: 3-5 years
Company Description
Akira Insights is a boutique pure-play Data & Analytics consulting firm providing services to Multinational corporations, Large enterprises, and Fortune 500s from various sectors helping businesses unlock valuable insights from their data.
Job Summary:
We are looking for a skilled Data Engineer with hands-on expertise in Databricks, Spark, and data transformation techniques. The ideal candidate will have a strong technical foundation in SQL, Python/Pyspark, and Spark Scala, with additional experience in Azure and data engineering tools preferred. This role involves building and optimizing scalable data pipelines, collaborating with stakeholders, and implementing best practices to enhance data processing performance and efficiency.
Key Responsibilities:
Data Pipeline Development:
- Design, develop, and optimize scalable data processing pipelines using Databricks and Spark.
- Build and maintain robust ETL workflows to handle large-scale data.
Data Optimization:
- Implement advanced Spark and SQL optimization techniques to ensure high performance and scalability.
- Utilize Databricks Delta Lake Architecture and Unity Catalog for effective data governance.
Data Transformation:
- Use SQL and Pyspark functions to manipulate, transform, and enrich data according to business requirements.
- Work with Spark Scala for additional data processing tasks as needed.
Collaboration and Communication:
- Collaborate with stakeholders, data analysts, and other teams to gather and understand data requirements.
- Effectively communicate technical concepts to non-technical stakeholders.
Required Skills:
- Spark Scala: Expertise in Spark-based application development.
- Databricks: Hands-on experience with Delta Lake Architecture and Unity Catalog.
- SQL: Advanced data transformation skills.
- Python/Pyspark: Proficiency in data manipulation and processing.
- Excellent communication skills.
Good to Have:
- Azure: Experience with Azure-based services and solutions.
- ETL: Hands-on experience with ETL processes and tools.
- Power BI: Experience in working with Power BI (preferred but optional).
- Familiarity with IntelliJ and version control systems like GIT.
Day-to-Day Activities:
- Develop, test, and deploy data pipelines and workflows using Spark and Databricks.
- Optimize SQL and Spark jobs for better performance and efficiency.
- Collaborate with stakeholders to gather data requirements and deliver solutions.
- Implement data governance practices using Databricks Unity Catalog.
Preferred Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- Certification in Azure or Databricks is a plus.
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