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Blumetra

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3.5

based on 26 Reviews

17 Blumetra Jobs

Lead Data Engineer - Indore

BLUMETRA SOLUTIONS INDIA PRIVATE LIMITED

3.5

based on 26 Reviews

7-12 years

Indore

1 vacancy

Lead Data Engineer - Indore

Blumetra

posted 4hr ago

Job Role Insights

Flexible timing

Key skills for the job

Python SQL Oracle Informatica SAP Business Intelligence MySQL

+ 3 more

Job Description

Blumetra Solutions is a US based Software Product Engineering firm headquartered in US, San Francisco and has a development center in Hyderabad, Indore, India.

We are specialized in providing Digital services like Data Management (MDM, Data Quality, Data Governance) & Data Analytics, Cloud, Business Applications and Quality Assurance, were partnered with our customers across different industries like Retail, financial services, high tech, pharmaceuticals, and other industries to help them achieve their digital transformation objectives.

Were platinum partners for Informatica, AWS, Snowflake, etc. and an ISO certified organization.

Position: Lead Data Engineer

Work Location: Indore - Hybrid

Experience - 7 to 10 years

Employment Type: Full time

No. of positions - 2

Please note, Candidates whore working in Indore (or) whose home town is Indore / nearby are preferable.

Job Description:

We are seeking a highly skilled and experienced Lead Data Engineer (7+ years) to join our dynamic team. As a Lead Data Engineer, you will play a crucial role in designing, developing, and maintaining our data infrastructure. You will be responsible for ensuring the efficient and reliable collection, storage, and transformation of large-scale data to support business intelligence, analytics, and data-driven decision-making.

Key Responsibilities:

Data Architecture & Design:

Lead the design and implementation of robust data architectures that support data warehousing (DWH), data integration, and analytics platforms.
Develop and maintain ETL (Extract, Transform, Load) pipelines to ensure the efficient processing of large datasets.

ETL Development:

Design, develop, and optimize ETL processes using tools like Informatica Power Center, Intelligent Data Management Cloud (IDMC), or custom Python scripts.
Implement data transformation and cleansing processes to ensure data quality and consistency across the enterprise.

Data Warehouse Development:

Build and maintain scalable data warehouse solutions using Snowflake, Databricks, Redshift, or similar technologies.
Ensure efficient storage, retrieval, and processing of structured and semi-structured data.

Big Data & Cloud Technologies:

Utilize AWS Glue and PySpark for large-scale data processing and transformation.
Implement and manage data pipelines using Apache Airflow for orchestration and scheduling.
Leverage cloud platforms (AWS, Azure, GCP) for data storage, processing, and analytics.

Data Management & Governance:

Establish and enforce data governance and security best practices.
Ensure data integrity, accuracy, and availability across all data platforms.
Implement monitoring and alerting systems to ensure data pipeline reliability.

Collaboration & Leadership:

Work closely with data Stewards, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs.
Mentor and guide junior data engineers, fostering a culture of continuous learning and development within the team.
Lead data-related projects from inception to delivery, ensuring alignment with business objectives and timelines.

Database Management:

Design and manage relational databases (RDBMS) to support transactional and analytical workloads.
Optimize SQL queries for performance and scalability across various database platforms.

Required Skills & Qualifications:

Education: Bachelors or Masters degree in Computer Science, Information Systems, Engineering, or a related field.
Experience: Minimum of 7+ years of experience in data engineering, ETL, and data warehouse development.
Proven experience with ETL tools like Informatica Power Center or IDMC.
Strong proficiency in Python and PySpark for data processing.
Experience with cloud-based data platforms such as AWS Glue, Snowflake, Databricks, or Redshift.
Hands-on experience with SQL and RDBMS platforms (e.g., Oracle, MySQL, PostgreSQL).
Familiarity with data orchestration tools like Apache Airflow.

Technical Skills:

Advanced knowledge of data warehousing concepts and best practices.
Strong understanding of data modeling, schema design, and data governance.
Proficiency in designing and implementing scalable ETL pipelines.
Experience with cloud infrastructure (AWS, Azure, GCP) for data storage and processing.

Soft Skills:

Excellent communication and collaboration skills.
Ability to lead and mentor a team of engineers.
Strong problem-solving and analytical thinking abilities.
Ability to manage multiple projects and prioritize tasks effectively.

Preferred Qualifications:

Experience with machine learning workflows and data science tools.
Certification in AWS, Snowflake, Databricks, or relevant data engineering technologies.
Experience with Agile methodologies and DevOps practices.

Employment Type: Full Time, Permanent

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