Data Engineer

This role is for one of Weekday’s clients
Salary range: Rs 1600000 - Rs 2500000 (ie INR 16 - 25 LPA)

Min Experience: 3+ years
Location: Gurugram, Haryana, India
JobType: full-time

We are looking for a skilled and detail-oriented Data Engineer with 3–5 years of experience in data engineering, data warehousing, and data management. The ideal candidate will have strong expertise in designing, developing, and maintaining scalable data pipelines and robust data warehouse solutions that support business intelligence, reporting, and analytics.

The candidate will be responsible for collecting, transforming, integrating, and organizing data from multiple sources to ensure its accuracy, consistency, and accessibility. This role requires a strong understanding of data warehousing concepts, ETL/ELT processes, database technologies, and data modeling. The Data Engineer will collaborate with data analysts, business stakeholders, and technical teams to build reliable data infrastructure and enable data-driven decision-making.

Requirements

Key Responsibilities

1. Data Warehousing

• Design, develop, and maintain scalable data warehouse solutions to support business reporting and analytical requirements.
• Build and optimize data models, including dimensional models, star schemas, and snowflake schemas.
• Develop and manage data structures, tables, views, and relationships to ensure efficient data storage and retrieval.
• Implement data integration processes to consolidate information from multiple operational systems and external sources.
• Monitor data warehouse performance and optimize queries, indexing, and storage for improved efficiency.
• Ensure data quality, consistency, integrity, and security across warehouse environments.

2. Data Pipeline Development

• Design, build, and maintain reliable ETL/ELT pipelines for extracting, transforming, and loading data.
• Develop automated workflows to process structured and semi-structured data from different sources.
• Identify and troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.
• Implement validation checks and monitoring mechanisms to ensure data accuracy and pipeline reliability.
• Document data flows, transformation logic, and technical processes for maintainability.

3. Data Engineering

• Develop scalable data processing solutions using appropriate programming languages and data technologies.
• Integrate data from databases, APIs, cloud platforms, and other business applications.
• Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
• Follow best practices for data governance, access control, security, and efficient data processing.
• Contribute to improving existing data architecture, automation, and engineering workflows.

4. Data Analysis and Business Support

• Work closely with data analysts and business teams to provide reliable, analysis-ready datasets.
• Support the development of dashboards, reports, and business intelligence solutions.
• Investigate data trends, anomalies, and discrepancies to identify potential data quality issues.
• Translate business requirements into appropriate data models and processing workflows.

Must-Have Skills

• Strong knowledge of Data Warehousing concepts and architecture.
• Experience with data modeling, ETL/ELT processes, and data integration.
• Proficiency in SQL and relational databases.
• Understanding of database performance optimization and data quality management.
• Strong analytical thinking, troubleshooting, and problem-solving abilities.

Good-to-Have Skills

• Experience in Data Engineering and building automated data pipelines.
• Knowledge of Data Analysis and business intelligence tools.
• Familiarity with Python or similar programming languages.
• Exposure to cloud data platforms and modern data warehouse technologies.
• Experience with workflow orchestration and data pipeline monitoring tools.

Qualifications and Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 3–5 years of relevant experience in data engineering, data warehousing, or database development.
• Strong communication skills and the ability to collaborate effectively with technical and non-technical stakeholders.