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Position: AWS Data Engineer

Experience: 5 to 7 Years

Location: Bengaluru, Pune, Chennai, Mumbai, Gurugram

Work Mode: Hybrid (3 days work from office per week)

Employment Type: Full-time

About the Role:

We are seeking a highly skilled and motivated AWS Data Engineer with 5–7 years of experience in building and optimizing data pipelines, architectures, and data sets. The ideal candidate will have strong experience with AWS services including Glue, Athena, Redshift, Lambda, DMS, RDS, and CloudFormation. You will be responsible for managing the full data lifecycle from ingestion to transformation and storage, ensuring efficiency and performance.

Key Responsibilities:

• Design, develop, and optimize scalable ETL pipelines using AWS Glue, Python/PySpark, and SQL.
• Work extensively with AWS services such as Glue, Athena, Lambda, DMS, RDS, Redshift, CloudFormation, and other serverless technologies.
• Implement and manage data lake and warehouse solutions using AWS Redshift and S3.
• Optimize data models and storage for cost-efficiency and performance.
• Write advanced SQL queries to support complex data analysis and reporting requirements.
• Collaborate with stakeholders to understand data requirements and translate them into scalable solutions.
• Ensure high data quality and integrity across platforms and processes.
• Implement CI/CD pipelines and best practices for infrastructure as code using CloudFormation or similar tools.

Required Skills & Experience:

• Strong hands-on experience with Python or PySpark for data processing.
• Deep knowledge of AWS Glue, Athena, Lambda, Redshift, RDS, DMS, and CloudFormation.
• Proficiency in writing complex SQL queries and optimizing them for performance.
• Familiarity with serverless architectures and AWS best practices.
• Experience in designing and maintaining robust data architectures and data lakes.
• Ability to troubleshoot and resolve data pipeline issues efficiently.
• Strong communication and stakeholder management skills.

Job Summary:

Seeking a seasoned SQL + ETL Developer with 4+ years of experience in managing large-scale datasets and cloud-based data pipelines. The ideal candidate is hands-on with MySQL, PySpark, AWS Glue, and ETL workflows, with proven expertise in AWS migration and performance optimization.

Key Responsibilities:

• Develop and optimize complex SQL queries and stored procedures to handle large datasets (100+ million records).
• Build and maintain scalable ETL pipelines using AWS Glue and PySpark.
• Work on data migration tasks in AWS environments.
• Monitor and improve database performance; automate key performance indicators and reports.
• Collaborate with cross-functional teams to support data integration and delivery requirements.
• Write shell scripts for automation and manage ETL jobs efficiently.

Required Skills:

• Strong experience with MySQL, complex SQL queries, and stored procedures.
• Hands-on experience with AWS Glue, PySpark, and ETL processes.
• Good understanding of AWS ecosystem and migration strategies.
• Proficiency in shell scripting.
• Strong communication and collaboration skills.

Nice to Have:

• Working knowledge of Python.
• Experience with AWS RDS.

Profile: AWS Data Engineer

Mode- Hybrid

Experience- 5+7 years

Locations - Bengaluru, Pune, Chennai, Mumbai, Gurugram

Roles and Responsibilities

• Design and maintain ETL pipelines using AWS Glue and Python/PySpark
• Optimize SQL queries for Redshift and Athena
• Develop Lambda functions for serverless data processing
• Configure AWS DMS for database migration and replication
• Implement infrastructure as code with CloudFormation
• Build optimized data models for performance
• Manage RDS databases and AWS service integrations
• Troubleshoot and improve data processing efficiency
• Gather requirements from business stakeholders
• Implement data quality checks and validation
• Document data pipelines and architecture
• Monitor workflows and implement alerting
• Keep current with AWS services and best practices

Required Technical Expertise:

• Python/PySpark for data processing
• AWS Glue for ETL operations
• Redshift and Athena for data querying
• AWS Lambda and serverless architecture
• AWS DMS and RDS management
• CloudFormation for infrastructure
• SQL optimization and performance tuning

Job Overview:

We are seeking an experienced AWS Data Engineer to join our growing data team. The ideal candidate will have hands-on experience with AWS Glue, Redshift, PySpark, and other AWS services to build robust, scalable data pipelines. This role is perfect for someone passionate about data engineering, automation, and cloud-native development.

Key Responsibilities:

• Design, build, and maintain scalable and efficient ETL pipelines using AWS Glue, PySpark, and related tools.
• Integrate data from diverse sources and ensure its quality, consistency, and reliability.
• Work with large datasets in structured and semi-structured formats across cloud-based data lakes and warehouses.
• Optimize and maintain data infrastructure, including Amazon Redshift, for high performance.
• Collaborate with data analysts, data scientists, and product teams to understand data requirements and deliver solutions.
• Automate data validation, transformation, and loading processes to support real-time and batch data processing.
• Monitor and troubleshoot data pipeline issues and ensure smooth operations in production environments.

Required Skills:

• 5 to 7 years of hands-on experience in data engineering roles.
• Strong proficiency in Python and PySpark for data transformation and scripting.
• Deep understanding and practical experience with AWS Glue, AWS Redshift, S3, and other AWS data services.
• Solid understanding of SQL and database optimization techniques.
• Experience working with large-scale data pipelines and high-volume data environments.
• Good knowledge of data modeling, warehousing, and performance tuning.

Preferred/Good to Have:

• Experience with workflow orchestration tools like Airflow or Step Functions.
• Familiarity with CI/CD for data pipelines.
• Knowledge of data governance and security best practices on AWS.

Role - ETL Developer

Work Mode - Hybrid

Experience- 4+ years

Location - Pune, Gurgaon, Bengaluru, Mumbai

Required Skills - AWS, AWS Glue, Pyspark, ETL, SQL

Required Skills:

• 4+ years of hands-on experience in MySQL, including SQL queries and procedure development
• Experience in Pyspark, AWS, AWS Glue
• Experience in AWS ,Migration
• Experience with automated scripting and tracking KPIs/metrics for database performance
• Proficiency in shell scripting and ETL.
• Strong communication skills and a collaborative team player
• Knowledge of Python and AWS RDS is a plus

Job Description: Data Engineer 

Position Overview:

Role Overview

We are seeking a skilled Python Data Engineer with expertise in designing and implementing data solutions using the AWS cloud platform. The ideal candidate will be responsible for building and maintaining scalable, efficient, and secure data pipelines while leveraging Python and AWS services to enable robust data analytics and decision-making processes.

Key Responsibilities

· Design, develop, and optimize data pipelines using Python and AWS services such as Glue, Lambda, S3, EMR, Redshift, Athena, and Kinesis.

· Implement ETL/ELT processes to extract, transform, and load data from various sources into centralized repositories (e.g., data lakes or data warehouses).

· Collaborate with cross-functional teams to understand business requirements and translate them into scalable data solutions.

· Monitor, troubleshoot, and enhance data workflows for performance and cost optimization.

· Ensure data quality and consistency by implementing validation and governance practices.

· Work on data security best practices in compliance with organizational policies and regulations.

· Automate repetitive data engineering tasks using Python scripts and frameworks.

· Leverage CI/CD pipelines for deployment of data workflows on AWS.

Work Mode: Hybrid

Need B.Tech, BE, M.Tech, ME candidates - Mandatory

Must-Have Skills:

● Educational Qualification :- B.Tech, BE, M.Tech, ME in any field.

● Minimum of 3 years of proven experience as a Data Engineer.

● Strong proficiency in Python programming language and SQL.

● Experience in DataBricks and setting up and managing data pipelines, data warehouses/lakes.

● Good comprehension and critical thinking skills.

● Kindly note Salary bracket will vary according to the exp. of the candidate - 

- Experience from 4 yrs to 6 yrs - Salary upto 22 LPA

- Experience from 5 yrs to 8 yrs - Salary upto 30 LPA

- Experience more than 8 yrs - Salary upto 40 LPA

We are looking for a skilled and passionate Data Engineers with a strong foundation in Python programming and hands-on experience working with APIs, AWS cloud, and modern development practices. The ideal candidate will have a keen interest in building scalable backend systems and working with big data tools like PySpark.

Key Responsibilities:

• Write clean, scalable, and efficient Python code.
• Work with Python frameworks such as PySpark for data processing.
• Design, develop, update, and maintain APIs (RESTful).
• Deploy and manage code using GitHub CI/CD pipelines.
• Collaborate with cross-functional teams to define, design, and ship new features.
• Work on AWS cloud services for application deployment and infrastructure.
• Basic database design and interaction with MySQL or DynamoDB.
• Debugging and troubleshooting application issues and performance bottlenecks.

Required Skills & Qualifications:

• 4+ years of hands-on experience with Python development.
• Proficient in Python basics with a strong problem-solving approach.
• Experience with AWS Cloud services (EC2, Lambda, S3, etc.).
• Good understanding of API development and integration.
• Knowledge of GitHub and CI/CD workflows.
• Experience in working with PySpark or similar big data frameworks.
• Basic knowledge of MySQL or DynamoDB.
• Excellent communication skills and a team-oriented mindset.

Nice to Have:

• Experience in containerization (Docker/Kubernetes).
• Familiarity with Agile/Scrum methodologies.

Key Responsibilities:

Design, develop, and optimize scalable data pipelines and ETL processes.

Work with large datasets using GCP services like BigQuery, Dataflow, and Cloud Storage.

Implement real-time data streaming and processing solutions using Pub/Sub and Dataproc.

Collaborate with cross-functional teams to ensure data quality and governance.

Technical Requirements:

4+ years of experience in Data Engineering.

Strong expertise in GCP services like Workflow,tensorflow, Dataproc, and Cloud Storage.

Proficiency in SQL and programming languages such as Python or Java

.Experience in designing and implementing data pipelines

and working with real-time data processing.

Familiarity with CI/CD pipelines and cloud security best practices.

Data Engineer + Integration engineer + Support specialistExp – 5-8 years

Necessary Skills:· SQL & Python / PySpark

· AWS Services: Glue, Appflow, Redshift

· Data warehousing

· Data modelling

Job Description:· Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform. Design/ implement, and maintain the data architecture for all AWS data services

· A strong understanding of data modelling, data structures, databases (Redshift), and ETL processes

· Work with stakeholders to identify business needs and requirements for data-related projects

Strong SQL and/or Python or PySpark knowledge

· Creating data models that can be used to extract information from various sources & store it in a usable format

· Optimize data models for performance and efficiency

· Write SQL queries to support data analysis and reporting

· Monitor and troubleshoot data pipelines

· Collaborate with software engineers to design and implement data-driven features

· Perform root cause analysis on data issues

· Maintain documentation of the data architecture and ETL processes

· Identifying opportunities to improve performance by improving database structure or indexing methods

· Maintaining existing applications by updating existing code or adding new features to meet new requirements

· Designing and implementing security measures to protect data from unauthorized access or misuse

· Recommending infrastructure changes to improve capacity or performance

Experience in Process industry

Data Engineer + Integration engineer + Support specialistExp – 3-5 years

Necessary Skills:· SQL & Python / PySpark

· AWS Services: Glue, Appflow, Redshift

· Data warehousing basics

· Data modelling basics

Job Description:· Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform.

· A strong understanding of data modelling, data structures, databases (Redshift)

Strong SQL and/or Python or PySpark knowledge

· Design and implement ETL processes to load data into the data warehouse

· Creating data models that can be used to extract information from various sources & store it in a usable format

· Optimize data models for performance and efficiency

· Write SQL queries to support data analysis and reporting

· Collaborate with team to design and implement data-driven features

· Monitor and troubleshoot data pipelines

· Perform root cause analysis on data issues

· Maintain documentation of the data architecture and ETL processes

· Maintaining existing applications by updating existing code or adding new features to meet new requirements

· Designing and implementing security measures to protect data from unauthorized access or misuse

· Identifying opportunities to improve performance by improving database structure or indexing methods

· Designing and implementing security measures to protect data from unauthorized access or misuse

· Recommending infrastructure changes to improve capacity or performance

Technical Skills:

• Ability to understand and translate business requirements into design.
• Proficient in AWS infrastructure components such as S3, IAM, VPC, EC2, and Redshift.
• Experience in creating ETL jobs using Python/PySpark.
• Proficiency in creating AWS Lambda functions for event-based jobs.
• Knowledge of automating ETL processes using AWS Step Functions.
• Competence in building data warehouses and loading data into them.

Responsibilities:

• Understand business requirements and translate them into design.
• Assess AWS infrastructure needs for development work.
• Develop ETL jobs using Python/PySpark to meet requirements.
• Implement AWS Lambda for event-based tasks.
• Automate ETL processes using AWS Step Functions.
• Build data warehouses and manage data loading.
• Engage with customers and stakeholders to articulate the benefits of proposed solutions and frameworks.

• Proficiency in shell scripting
• Proficiency in automation of tasks
• Proficiency in Pyspark/Python
• Proficiency in writing and understanding of sqoop
• Understanding of CloudEra manager
• Good understanding of RDBMS
• Good understanding of Excel

• Minimum 1 years of relevant experience, in PySpark (mandatory)
• Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus 
• Ability to play lead role and independently manage 3-5 member of Pyspark development team 
• EMR ,Python and PYspark mandate.
• Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS