This role is for one of our clients
Industry: IT Services and IT Consulting

Seniority level: Mid-Senior level

Experience: 7+ yrs

Location: Bengaluru, Pune

Job Type: full-time

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We are looking for a highly experienced Senior Data Engineer to design, build, and optimize scalable cloud-based data platforms that power enterprise analytics, reporting, and AI-driven initiatives. This role is ideal for a hands-on data engineering professional who combines deep technical expertise with strong business understanding to create reliable, secure, and high-performance data solutions. You will be responsible for developing modern data architectures, building robust ETL/ELT frameworks, and leveraging cloud-native technologies to support large-scale data processing and analytics. Working closely with business stakeholders, data scientists, analysts, and engineering teams, you will transform complex business requirements into scalable technical solutions while driving best practices in data engineering, governance, performance optimization, and platform reliability.

Requirements
Key Responsibilities

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data integration frameworks
Build cloud-native data solutions using AWS services such as Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, and S3
Develop and optimize large-scale data processing workflows using Python, PySpark, SQL, and PL/SQL
Design and implement enterprise data warehouses, data marts, dimensional models, and reporting structures
Collaborate with business stakeholders, product teams, analysts, and data scientists to deliver data-driven solutions
Ensure data quality, governance, security, compliance, and lifecycle management across the data ecosystem
Optimize database performance, query execution, and high-volume data processing workloads
Implement monitoring, logging, alerting, and troubleshooting mechanisms to maintain platform reliability
Participate in architecture reviews, cloud modernization initiatives, and technical design discussions
Support AI, machine learning, and advanced analytics use cases through scalable data infrastructure
Drive continuous improvement initiatives focused on performance, scalability, and operational excellence
Mentor junior engineers and promote engineering best practices, code quality standards, and knowledge sharing
Support deployment activities, production issue resolution, and ongoing platform enhancements

What Makes You a Great Fit

8-10 years of experience in Data Engineering, Data Warehousing, and Cloud Data Platform development
Strong expertise in AWS cloud services, including Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, and S3
Advanced proficiency in Python and PySpark for large-scale data processing and transformation
Strong command of SQL and PL/SQL development and optimization
Extensive experience building ETL/ELT pipelines, data ingestion frameworks, and integration solutions
Deep understanding of data warehousing concepts, dimensional modeling, and database architecture
Experience working with structured, semi-structured, and unstructured datasets
Strong knowledge of modern data architectures, including Data Lakes, Data Warehouses, and Lakehouse environments
Familiarity with workflow orchestration, event-driven architectures, and distributed data processing systems
Experience implementing data governance, quality frameworks, and security best practices
Strong analytical thinking, problem-solving skills, and attention to detail
Excellent communication and stakeholder management abilities
Experience supporting AI, Machine Learning, Data Science, or Advanced Analytics initiatives is highly desirable
Exposure to CI/CD pipelines, DevOps practices, Infrastructure as Code (IaC), and Agile delivery methodologies is a plus
AWS certifications or equivalent cloud credentials are highly valued
A proactive, ownership-driven mindset with a passion for building scalable and reliable data platforms

Lead AWS Data Engineer