JMAN Group - Data Engineering Architect ( 0-0 yrs )

ETCIO - Cloud Data Center; Chennai District; On-site; INR 800,000 - 1,200,000; Full time

Benefits offered by this job

Competitive annual bonus

Market-leading private health insurance

Regular company socials

Annual company away days

Extensive training opportunities

Job summary

ETCIO - Cloud Data Center in Chennai is looking for a Data Engineer to lead a team providing guidance and mentorship. You'll be responsible for building data pipeline tools, ensuring coding standards, and overseeing data quality and operational processes.

The ideal candidate has strong experience with ETL/ELT tools, proficiency in SQL, and familiarity with cloud platforms like AWS and Azure. Outstanding benefits include competitive bonuses and extensive training opportunities.

Qualifications

• Strong experience in ETL/ELT or building data pipeline tools.
• Hands-on experience with data warehouse/platforms.
• Proficiency in SQL and experience with relational databases.

Responsibilities

• Manage and lead a team of data engineers.
• Build analytics tools for actionable insights.
• Oversee the development and maintenance of data pipelines.

Skills

ETL/ELT experience

GIT for version control

Data warehouse/platform experience

SQL proficiency

Data visualization tools

SaaS integration

Cloud platforms (AWS, Azure, GCP)

Python and PySpark

Tools

AWS Glue

Azure Data Factory

Power BI

Tableau

Snowflake

Job description

Responsibilities

• Manage and lead a team of data engineers, providing guidance, mentorship, and fostering a collaborative environment to maximize team performance.
• Diagnose existing architecture and data maturity and help the organization identify gaps and possible solutions.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Ensure coding standards and develop test cases, queries, and validations for all developed features.
• Apply data governance, metadata management, and data quality practices.
• Evaluate and recommend cloud data platforms for customer needs with optimal solutions.
• Provide guidance and monitoring of the team on end‑to‑end operational processes.
• Perform dimensional modeling and business domain conversion using dimensional modeling / Data Vault design patterns.
• Oversee the development and maintenance of data pipelines, ensuring data quality, reliability, security, and scalability.

Qualifications

• Strong experience in ETL/ELT or building data pipeline tools such as AWS Glue, Azure Data Factory, Synapse, Matillion, dbt.
• Ability to use GIT for version control and maintain versions of data models.
• Hands‑on experience with data warehouse/platforms such as Azure SQL Server, Redshift, BigQuery, Databricks, Snowflake.
• Strong proficiency in writing SQL queries, database query optimization, and stored procedures.
• Familiarity with data visualization tools like Power BI, Tableau, Looker.
• Integration experience with SaaS‑based CRM, accounting and financial systems such as HubSpot, Salesforce, NetSuite, Zoho.
• Experience in end‑to‑end deployment process from understanding business requirements to implementation.
• Expertise in data solution architecture and tools/techniques used for data management; constructs and implements operational data store and data marts.
• Strong proficiency in Python and PySpark.
• Knowledge of SDLC, Agile Scrum methodologies.
• Experience in budgeting, service cost, and product migration from legacy to modernized application.
• Proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL.
• Experience with NoSQL databases such as MongoDB, Cassandra, or DynamoDB is a plus.
• Experience with on‑premises and cloud‑based databases and lakes.
• Proven experience as a data engineer with a focus on cloud platforms (AWS, Azure, GCP).
• Experience in full‑stack technology is a plus.
• Hands‑on experience in taking ownership of design patterns and best practices in data modeling and implementation strategy.
• Ability to identify opportunities for automation and implement tools to streamline data engineering workflows.
• Ensure compliance with data governance policies, data privacy regulations, and industry best practices.
• Ability to work collaboratively with CoE leadership and business units.

Other Skills

• Ready to learn, adopt, and implement state‑of‑the‑art evolving open‑source technologies to provide breakthrough business solutions.
• Build moderately complex prototypes to test new concepts and provide ideas on reusable frameworks, components, and data products or solutions and help promote adoption of new technologies.
• Promote a culture of continuous learning, sharing knowledge, and keep abreast of emerging data engineering technology.

Benefits

• Competitive annual bonus
• Market‑leading private health insurance
• Regular company socials
• Annual company away days
• Extensive training opportunities