The Role
Design, build, and deploy end-to-end data pipelines and ETL/ELT solutions on Databricks. Integrate diverse data sources, implement Spark (PySpark/Scala) transformations, optimize SQL queries, maintain data models, build APIs/data services, ensure data quality/security, monitor/optimize pipeline performance in cloud environments, and follow CI/CD and governance practices.
Summary Generated by Built In
We are seeking an experienced Full Stack Data Engineer with 5–6 years of industry
experience. The ideal candidate will have a proven track record of working on live projects,
preferably within the manufacturing or energy sectors. He/she will play a key role in developing,
and maintaining scalable data solutions using Databricks and related technologies.
Key Responsibilities:
- Develop, and deploy end-to-end data pipelines and solutions on Databricks, integrating with
- various data sources and systems.
- Collaborate with cross-functional teams to understand data, and deliver effective BI
- solutions.
- Implement data ingestion, transformation, and processing workflows using Spark
- (PySpark/Scala), SQL, and Databricks notebooks.
- Develop and maintain data models, ETL/ELT processes ensuring high performance,
- reliability, scalability and data quality.
- Build and maintain APIs and data services to support analytics, reporting, and application
- integration.
- Ensure data quality, integrity, and security across all stages of the data lifecycle.
- Monitor, troubleshoot, and optimize pipeline performance in a cloud-based environment.
- Write clean, modular, and well-documented Python/Scala/SQL/PySpark code.
- Integrate data from various sources, including APIs, relational and non-relational databases,
- IoT devices, and external data providers.
- Ensure adherence to data governance, security, and compliance policies.
Required Skills and Experience:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 5-6 years of hands-on experience in data engineering, with a strong focus on Databricks and
- Apache Spark.
- Strong programming skills in Python/PySpark and/or Scala, with a deep understanding of
- Apache Spark.
- Experience with Azure Databricks.
- Strong SQL skills for data manipulation, analysis, and performance tuning.
- Strong understanding of data structures and algorithms, with the ability to apply them to
- optimize code and implement efficient solutions.
- Strong understanding of data architecture, data modeling, ETL/ELT processes, and data
- warehousing concepts.
- Experience building and maintaining ETL/ELT pipelines in production environments.
- Familiarity with Delta Lake, Unity Catalog, or similar technologies.
- Experience working with structured and unstructured data, including JSON, Parquet, Avro,
- and time-series data.
- Familiarity with CI/CD pipelines and tools like Azure DevOps, version control (Git), and
- DevOps practices for data engineering.
- Excellent problem-solving skills, attention to detail, and ability to work independently or as
- part of a team.
- Strong communication skills to interact with technical and non-technical stakeholders.
Requirements
- Experience with Delta Lake and Databricks Workflows.
- Exposure to real-time data processing and streaming technologies (Kafka, Spark Streaming).
- Exposure to data visualization tool Databricks Genie for data analysis and reporting.
- Knowledge of data governance, security, and compliance best practices.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 5-6 years hands-on experience in data engineering
- Experience with Databricks and Apache Spark
- Strong programming skills in Python/PySpark and/or Scala
- Experience with Azure Databricks
- Strong SQL skills for data manipulation, analysis, and performance tuning
- Understanding of data structures and algorithms to optimize code
- Experience with data architecture, data modeling, ETL/ELT processes, and data warehousing
- Experience building and maintaining production ETL/ELT pipelines
- Familiarity with Delta Lake and Unity Catalog
- Experience working with JSON, Parquet, Avro, and time-series data
- Familiarity with CI/CD pipelines, Azure DevOps, and version control (Git)
- Experience developing and maintaining APIs and data services
- Experience with Databricks Workflows and Databricks Notebooks
- Exposure to real-time data processing and streaming technologies (Kafka, Spark Streaming)
- Exposure to Databricks Genie for data analysis and reporting
- Knowledge of data governance, security, and compliance best practices
- Ability to write clean, modular, well-documented Python/Scala/SQL/PySpark code
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The Company
What We Do
Koantek is a Databricks-exclusive system integrator focused on enterprise-scale data and AI transformation, helping clients modernize, migrate, and scale AI solutions.
