Data Engineer

Job Title: Data Engineer Job Type: Full Time, Permanent Job Location: Noida/Hyderabad Reports to: Manager Qualifications: BE/B.Tech/MCA Degree in Computer Science, Engineering, similar relevant field Total Experience : 3+ Years Working Model : Work from Office

ABOUT THE ROLE We are seeking a skilled Data Engineer/ Senior Data Engineer to design, build, and maintain robust data infrastructure and pipelines that enable our organizaon to leverage data for strategic decision- making. The ideal candidate will have strong technical experse in data engineering, cloud technologies, and data architecture, with a passion for building scalable.

Key Roles & Responsbilities:

• Translate business requirements into technical specifications for data solutions
• Develop and maintain data models and schema designs that support analytical and operational needs

• Implement and manage data warehousing solutions on platforms like Amazon Redshift or Snowflake

• Design and implement middleware solutions to enable seamless data flows between applications and systems
• Design, develop, and maintain scalable ETL/ELT pipelines to ingest, process, and transform data from various sources
• Build automated data workflows using orchestration frameworks like Apache Airflow to ensure reliable and timely data delivery
• Process large-scale datasets using distributed computing frameworks, particularly Apache Spark
• Perform complex data wrangling and transformation tasks using Python libraries (Pandas, NumPy) and Spark DataFrames
• Work with geospatial (GIS) data, understanding spatial data types, coordinate systems, and GIS-specific processing requirements
• Optimize existing pipelines for performance, cost-efficiency, and maintainability
• Optimize cloud resource utilization to balance performance and cost
• Create and maintain documentation for data pipelines, data models, and technical processes

Key Skills required:

Technical Skills

Programming & Scripting:

• Advanced proficiency in Python for data engineering tasks, including experience with libraries such as Pandas, NumPy.

• Expert-level SQL skills with ability to write complex queries, optimize query performance, and design efficient database schemas

• Experience with version control systems (Git) and collaborative development practices

Data Integration & ETL/ELT:

• Hands-on experience in building and maintaining ETL/ELT pipelines

• Proficiency with Apache Spark for distributed data processing

• Experience with workflow orchestration tools, particularly Apache Airflow

• Strong understanding of API design and integration patterns (REST, GraphQL)

• Knowledge of message queuing systems (Kafka, RabbitMQ) is a plus

Data Storage & Management:

• Experience with SQL/NoSQL databases and understanding of when to use each type

• Hands-on experience with data warehousing platforms such as Amazon Redshift or Snowflake • Knowledge of or experience working with geospatial (GIS) data.

• Understanding of data modeling techniques (dimensional modeling, normalization, denormalization)

Cloud & Distributed Computing:

• Experience with AWS cloud platform and managed data services (S3, Redshift, Glue, Lambda, RDS)

• Experience with distributed computing frameworks and big data technologies

• Understanding of cloud cost optimization and resource management

Data Quality & Governance:

• Strong expertise in data cleaning, validation, and quality assurance techniques

• Experience with data profiling tools and methodologies

• Understanding of data governance principles and best practices

• Ability to implement data lineage and metadata management solutions

Reporting & Visualization:

• Experience working with BI tools, particularly Power BI

• Ability to design data models that support efficient reporting and visualization