Assistant Manager

Jobtailor; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Jobtailor is seeking an experienced Data Engineer to design, develop, and maintain scalable ETL/ELT pipelines. You will build data models, warehouses, lakes, and modern architectures using cloud-native tools.

You will ensure data quality and governance while collaborating with analytics, data science, and business teams to meet data requirements and drive performance. Mentorship and architecture discussions are part of the role.

Qualifications

• Bachelor's or Master's degree in CS/IT/Engineering/Data Science or related field.
• 5-8 years of experience in Data Engineering, Data Warehousing, or related domains.
• Strong SQL and Python for data processing and automation.
• Experience with Azure, AWS, or GCP cloud platforms.
• Hands-on experience with data integration and orchestration tools.
• Knowledge of modern data platforms (Databricks, Snowflake, Redshift, BigQuery).
• Experience with Spark/PySpark and large-scale data processing.
• Understanding of data modeling, ETL/ELT concepts, and DB optimization.
• Familiarity with DevOps, CI/CD, and version control.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build and optimize data models, warehouses, lakes, and architectures.
• Develop ingestion, transformation, and integration using cloud-native tech.
• Ensure data quality, integrity, reliability, and governance.
• Collaborate with business, analytics, and data science teams.
• Implement monitoring, troubleshooting, and performance optimization.
• Support real-time and batch data processing.
• Automate data workflows and deployment using CI/CD.
• Ensure compliance with security and data standards.
• Mentor junior team members and participate in architecture discussions.

Skills

ETL/ELT Pipelines

SQL Proficiency

Python Programming

Data Modeling

Cloud Data Processing

Spark/PySpark

Data Governance

CI/CD

Data Warehousing

Education

Bachelor's or Master's in Computer Science/IT/Engineering/Data Science

Tools

Azure Data Factory

Airflow

Informatica

Databricks

Snowflake

Redshift

BigQuery

CI/CD Tools

Version Control

Job description

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data models, data warehouses, data lakes, and modern data architectures.
• Develop data ingestion, transformation, and integration processes using cloud-native technologies.
• Ensure data quality, integrity, reliability, and governance across enterprise data assets.
• Collaborate with business, analytics, and data science teams to understand and deliver data requirements.
• Implement data pipeline monitoring, troubleshooting, and performance optimization procedures.
• Support real-time and batch data processing requirements.
• Automate data workflows and deployment processes using CI/CD best practices.
• Ensure compliance with security, privacy, and organizational data standards.
• Mentor junior team members and provide technical guidance on data engineering best practices.
• Participate in architecture discussions and recommend enhancements to improve scalability and efficiency.

Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• 5-8 years of experience in Data Engineering, Data Warehousing, or related domains.
• Strong proficiency in SQL and Python for data processing and automation.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Hands-on experience with data integration and orchestration tools such as Azure Data Factory, Airflow, Informatica, or similar platforms.
• Knowledge of modern data platforms including Databricks, Snowflake, Redshift, BigQuery, or equivalent technologies.
• Experience with Spark/PySpark and large-scale data processing frameworks.
• Strong understanding of data modeling, ETL/ELT concepts, and database optimization techniques.
• Familiarity with DevOps, CI/CD practices, and version control systems.
• Excellent analytical, problem-solving, stakeholder management, and communication skills.
• Experience leading projects or mentoring team members will be preferred.

Core Competencies

Demonstrates expertise in designing and developing scalable ETL/ELT pipelines, data modeling, and cloud-native data integration processes. Proficient in ensuring data quality and governance while collaborating with cross-functional teams to meet data requirements.

Highest-signal resume keywords

• ETL/ELT Pipeline Development
• SQL Proficiency
• Cloud Platform Experience (Azure, AWS, GCP)
• Data Integration Tools (Azure Data Factory, Airflow)
• Data Modeling and Database Optimization

Hard Skills

• ETL/ELT Pipeline Development
• SQL Proficiency
• Python Programming
• Data Modeling
• Database Optimization
• Data Integration
• Data Warehousing
• Data Governance
• Spark/PySpark
• Cloud Data Processing

Soft Skills

• Analytical Skills
• Problem-Solving
• Stakeholder Management
• Communication Skills
• Mentoring

Industry Keywords

• Data Engineering
• Data Warehousing
• Data Lakes
• Data Architecture
• Data Quality
• Data Integrity
• Data Processing
• Cloud-Native Technologies
• Real-Time Data Processing
• Batch Data Processing

Tools & Technologies

• Azure Data Factory
• Airflow
• Informatica
• Databricks
• Snowflake
• Redshift
• BigQuery
• CI/CD Practices
• Version Control Systems