Job Description
Job Title : Data Engineer
Job Description
As a Data Engineer, you will be part of a dynamic team responsible for developing and maintaining data pipelines, databases, and analytical systems @Kotak811
You will work closely with other data engineers, data scientists, and business stakeholders to ensure data integrity, availability, and reliability.
You should have expertise in designing, implementing, and operating stable, scalable, solutions to flow data from production systems into analytical data platform (big data tech stack) and into end-user facing applications for both real-time and batch use cases
Responsibilities
Data Ingestion and Integration
Collaborate with cross-functional teams to gather data requirements and identify data sources.
Design, develop, and maintain data ingestion pipelines from various structured and unstructured sources.
Implement data integration processes to ensure data quality and consistency.
Monitor and troubleshoot data ingestion issues and optimise performance.
Data Transformation and ETL:
Translate business requirements into technical specifications (data models)
Extract, transform, and load data from diverse sources into appropriate data models and structures.
Develop and maintain ETL workflows and processes using tools like Apache Spark, Apache Kafka, or other data integration frameworks.
Cleanse, validate, and transform data to meet business and analytical requirements.
Strong engineering mindset - build automated monitoring, alerting, self healing (restartability/graceful failures) features while building the consumption pipelines
Database Management:
Create and maintain scalable and efficient data storage systems, including relational databases, data warehouses, or NoSQL databases.
Optimise database performance, including indexing, partitioning, and query optimization.
Implement data security and access controls to ensure data privacy and compliance with industry regulations.
Monitor database health, performance, and capacity, and take proactive measures to ensure optimal system operation.
Data Governance and Documentation:
Ensure adherence to data management policies and standards.
Document data pipelines, ETL processes, and data flows to facilitate knowledge sharing and maintain data lineage.
Contribute to the development and maintenance of data dictionaries, data catalogues, and metadata repositories.
Participate in data quality initiatives and data governance reviews to maintain high data integrity.
Collaboration and Communication:
Collaborate effectively with cross-functional teams, including data scientists, business analysts, and software engineers.
Communicate technical concepts and solutions to both technical and non-technical stakeholders.
Participate in team meetings, code reviews, and knowledge-sharing sessions to foster a collaborative work environment.
Stay up-to-date with emerging technologies, industry trends, and best practices in data engineering.
Qualifications
2-3 years’ experience with a Bachelor's Degree in Computer Science, Engineering, Technology or related field required.
Proficiency in one or more programming languages such as Python, Java, or Scala.
Good knowledge of Agile, SDLC/CICD practices and tools
Experience with data integration tools and frameworks such as Apache Spark, Apache Kafka, or similar.
Experience is leveraging Cloud / OSS Data platform to build scalable data models and data pipelines for analytical, data science, systemic consumption use cases
Must have good knowledge of performance tuning/optimising data processing jobs, debugging time consuming jobs.
Good understanding of distributed systems
Experience working extensively in multi-petabyte DW environment
Strong problem-solving skills and attention to detail.
Job Description
As a Data Engineer, you will be part of a dynamic team responsible for developing and maintaining data pipelines, databases, and analytical systems @Kotak811
You will work closely with other data engineers, data scientists, and business stakeholders to ensure data integrity, availability, and reliability.
You should have expertise in designing, implementing, and operating stable, scalable, solutions to flow data from production systems into analytical data platform (big data tech stack) and into end-user facing applications for both real-time and batch use cases
Responsibilities
Data Ingestion and Integration
Collaborate with cross-functional teams to gather data requirements and identify data sources.
Design, develop, and maintain data ingestion pipelines from various structured and unstructured sources.
Implement data integration processes to ensure data quality and consistency.
Monitor and troubleshoot data ingestion issues and optimise performance.
Data Transformation and ETL:
Translate business requirements into technical specifications (data models)
Extract, transform, and load data from diverse sources into appropriate data models and structures.
Develop and maintain ETL workflows and processes using tools like Apache Spark, Apache Kafka, or other data integration frameworks.
Cleanse, validate, and transform data to meet business and analytical requirements.
Strong engineering mindset - build automated monitoring, alerting, self healing (restartability/graceful failures) features while building the consumption pipelines
Database Management:
Create and maintain scalable and efficient data storage systems, including relational databases, data warehouses, or NoSQL databases.
Optimise database performance, including indexing, partitioning, and query optimization.
Implement data security and access controls to ensure data privacy and compliance with industry regulations.
Monitor database health, performance, and capacity, and take proactive measures to ensure optimal system operation.
Data Governance and Documentation:
Ensure adherence to data management policies and standards.
Document data pipelines, ETL processes, and data flows to facilitate knowledge sharing and maintain data lineage.
Contribute to the development and maintenance of data dictionaries, data catalogues, and metadata repositories.
Participate in data quality initiatives and data governance reviews to maintain high data integrity.
Collaboration and Communication:
Collaborate effectively with cross-functional teams, including data scientists, business analysts, and software engineers.
Communicate technical concepts and solutions to both technical and non-technical stakeholders.
Participate in team meetings, code reviews, and knowledge-sharing sessions to foster a collaborative work environment.
Stay up-to-date with emerging technologies, industry trends, and best practices in data engineering.
Qualifications
2-3 years’ experience with a Bachelor's Degree in Computer Science, Engineering, Technology or related field required.
Proficiency in one or more programming languages such as Python, Java, or Scala.
Good knowledge of Agile, SDLC/CICD practices and tools
Experience with data integration tools and frameworks such as Apache Spark, Apache Kafka, or similar.
Experience is leveraging Cloud / OSS Data platform to build scalable data models and data pipelines for analytical, data science, systemic consumption use cases
Must have good knowledge of performance tuning/optimising data processing jobs, debugging time consuming jobs.
Good understanding of distributed systems
Experience working extensively in multi-petabyte DW environment
Strong problem-solving skills and attention to detail.
💡 Quick Summary
Seeking a career-building opportunity? The Data Engineer-Digital Banking Kotak 811-Regional Sales position is now open for candidates interested in the Bank Jobs sector. This role in Bangalore offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Bank Jobs is a plus.
