AWS Data Engineer - VOIS
Pune, MH, IN
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign, develop and maintain ETL and data pipelines using AWS Glue, Spark, Redshift and S3
Build and optimise data warehouse and data lake solutions
Create and maintain data models for reporting, analytics and BI
Investigate and resolve data quality issues with business and technical stakeholders
Automate repetitive activities and build reusable data frameworks
From the employer’s posting
Design, develop and maintain scalable ETL and data pipelines using AWS Glue, Apache Spark, Amazon Redshift, Amazon S3 and related AWS services.
Build and optimise data warehousing and data lake solutions to support analytical and operational business requirements.
Create and maintain robust data models that support reporting, analytics and business intelligence needs.
Perform data quality analysis, root cause investigation and resolution in collaboration with business and technical stakeholders.
Automate repetitive activities and create reusable frameworks that improve efficiency and consistency.
Tools in this posting
- Python
- SQL
- AWS
- Iceberg
- Redshift
- S3
- Spark
Source — Tool mentions in context
## What you’ll do Design, develop and maintain scalable ETL and data pipelines using AWS Glue, Apache Spark, Amazon Redshift, Amazon S3 and related AWS services. Build and optimise data warehousing and data lake solutions to support analytical and operational business requirements. Develop applications and data processing solutions using Python, SQL and cloud-native technologies. Create and maintain robust data models that support reporting, analytics and business intelligence needs. Perform data quality analysis, root cause investigation and resolution in collaboration with business and technical stakeholders. Develop proof-of-concept solutions to evaluate and implement innovative data engineering approaches. Support the operation and ongoing maintenance of data services to ensure reliability, scalability and performance. Automate repetitive activities and create reusable frameworks that improve efficiency and consistency. Work closely with cross-functional teams to design and deliver data products that support marketing and other business functions. Manage source code, deployments and releases using GitHub and CI/CD practices. Leverage tools such as Athena, Apache Iceberg, APIs and JSON-based integrations to support modern data architectures. Contribute to process improvements, operational excellence and continuous service enhancement initiatives. Exposure to Amazon QuickSight for dashboard development and data visualisation will be advantageous. ## Who you are
## Who you are 7 to 10+ years of relevant experience in Data Warehousing and Data Engineering. Strong hands-on experience with AWS Glue, Python, Apache Spark, Amazon Redshift, Amazon Athena and Apache Iceberg. Proven experience designing, developing and supporting enterprise-scale ETL pipelines. Strong understanding of data modelling concepts and best practices. Experience with GitHub, CI/CD practices, API integrations and JSON processing. Familiarity with ITSM processes and tools such as JIRA. Knowledge of telecom business processes and data domains is desirable. Excellent analytical, problem-solving and stakeholder management skills. Ability to work effectively within geographically distributed and multicultural teams. Strong verbal and written communication skills in English. ## Not a perfect fit?
## About this Role We are seeking an experienced AWS Data Engineer to design, build and support scalable cloud-based data solutions that enable data-driven decision making across the business. This role will focus on developing and maintaining data pipelines, creating data models, supporting data quality initiatives, and delivering innovative solutions using AWS technologies. The successful candidate will collaborate with global stakeholders and contribute to the continuous improvement of modern data platforms and services. ## What you’ll do
## What's in it for you Opportunity to work on large-scale cloud data platforms within a global telecommunications environment. Exposure to modern AWS-native data engineering technologies and architectures. Collaboration with international stakeholders and cross-functional teams across multiple markets. Opportunity to contribute to innovative proof-of-concept initiatives and data transformation programmes. Experience working in a highly collaborative environment focused on continuous improvement, automation and operational excellence. Exposure to global data governance, data quality and enterprise analytics practices. ## What skills you will learn
## What skills you will learn Advanced cloud data engineering practices across the AWS ecosystem. Enterprise-scale data warehousing and data lake architecture design. Data governance, data quality management and root cause analysis methodologies. Modern DevOps and CI/CD approaches for data platforms. Cross-functional stakeholder engagement within a large global organisation. Telecom analytics and business data domain knowledge. Scalable data modelling and performance optimisation techniques. ## VOIS Equal Opportunity Employer Commitment
Posting record
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- Live
- First seen by us
- Sep 30, 2026 · 29 days ago
- Recorded sightings
- 164
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Sep 22, 2026
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- Location & working pattern
Pune, MH, IN
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## VOIS Equal Opportunity Employer Commitment Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender identity, gender expression, sexual orientation, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background. ## Join Us
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