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Senior Data Engineer

Senior Data Engineer

Bajaj Finance

4 - 6 years

4 - 8 Lacs

pune

Posted:15 hours ago| Platform:

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Skills Required

data modeling etl elt pipeline data warehousing concepts continuous integration scala amazon redshift ci/cd data warehousing sql java postgresql spark gcp mysql hadoop bigquery snowflake python microsoft azure sql server data bricks kafka aws

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Purpose

The Senior Data Engineer will be responsible for designing, building, and maintaining scalable and efficient data pipelines and architectures for the Enterprise Data Platform. This role will focus on enabling high-quality, reliable, and timely data access for analytics, reporting, and business decision-making. Working closely with business analysts, data scientists, and architects, the Senior Data Engineer will ensure data solutions meet business needs and adhere to best practices and governance standards.

Duties and Responsibilities

Design and implement robust, scalable, and high-performance data pipelines and ETL/ELT processes.

Develop, optimize, and maintain data architectures including databases, data lakes, and data warehouses.

Ensure the quality, integrity, and security of data through robust data validation and data quality frameworks.

Collaborate with business analysts and stakeholders to understand business data requirements and translate them into technical designs.

Work closely with data architects to align with enterprise architecture standards and strategies.

Implement data integration solutions with various internal and external data sources.

Monitor, troubleshoot, and optimize system performance and data workflows.

Support the migration of on-premise data solutions to cloud-based environments (e.g., AWS, Azure, GCP).

Stay up to date with the latest industry trends and technologies in data engineering and recommend innovative solutions.

Create and maintain comprehensive documentation for all developed data pipelines and systems.

Mentor junior data engineers and contribute to the development of best practices.

Key Decisions / Dimensions

Selecting appropriate technologies, tools, and frameworks for data pipeline development.

Designing data models and database schemas that optimize for both performance and scalability.

Establishing standards for code quality, data validation, and monitoring processes.

Identifying performance bottlenecks and recommending architectural improvements.

Major Challenges

Managing and processing large volumes of structured and unstructured data with efficiency.

Designing systems that can handle scaling needs as business requirements and data volumes grow.

Balancing the need for quick delivery with the necessity for scalable and maintainable code.

Ensuring data quality and compliance with data governance and security policies.

Integrating disparate data sources with differing formats and standards into unified models.

Required Qualifications and Experiencea)

Qualifications

Bachelors Degree in Computer Engineering, Computer Science, Information Technology, or a related field.

Professional certifications such as Google Professional Data Engineer, AWS Certified Data Analytics Specialty, or Microsoft Certified: Azure Data Engineer Associate are a plus.b)Work Experience

Minimum of 4+ years of experience in data engineering or a related role.

Strong expertise in building and optimizing ETL/ELT pipelines and data workflows.

Proficient in programming languages such as Python, Java, or Scala.

Hands-on experience with SQL and relational database systems (e.g., PostgreSQL, SQL Server, MySQL).

Experience with big data technologies (e.g., Hadoop, Spark, Kafka).

Familiarity with cloud platforms (AWS, Azure, GCP) and cloud-native data services (e.g., Redshift, BigQuery, Snowflake, Databricks).

Solid understanding of data modeling, data warehousing concepts, and best practices.

Knowledge of CI/CD pipelines and infrastructure-as-code (IaC) is a plus.

Strong problem-solving s and the ability to work independently or in a team. c)s

Data Architecture

Delivery Management

Project Management

Cloud Data Platforms (e.g., Azure, AWS, GCP)

Data Modeling

Data Governance

Stakeholder Management

Quality Assurance

Agile Methodology

Team Leadership

Budget Management

Risk Management

Data IntegrationScalable Data Solutions

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Senior Data Engineer