Data Engineer at AI-powered cloud-based SaaS solution · Bengaluru (Bangalore) · 2 - 10 years · ₹15L - ₹50L / yr · Posted 24 Mar 2022

● Able contribute to the gathering of functional requirements, developing technical
specifications, and project & test planning
● Demonstrating technical expertise, and solving challenging programming and design
problems
● Roughly 80% hands-on coding
● Generate technical documentation and PowerPoint presentations to communicate
architectural and design options, and educate development teams and business users
● Resolve defects/bugs during QA testing, pre-production, production, and post-release
patches
● Work cross-functionally with various bidgely teams including: product management,
QA/QE, various product lines, and/or business units to drive forward results
Requirements
● BS/MS in computer science or equivalent work experience
● 2-4 years’ experience designing and developing applications in Data Engineering
● Hands-on experience with Big data Eco Systems.
● Hadoop,Hdfs,Map Reduce,YARN,AWS Cloud, EMR, S3, Spark, Cassandra, Kafka,
Zookeeper
● Expertise with any of the following Object-Oriented Languages (OOD): Java/J2EE,Scala,
Python
● Strong leadership experience: Leading meetings, presenting if required
● Excellent communication skills: Demonstrated ability to explain complex technical
issues to both technical and non-technical audiences
● Expertise in the Software design/architecture process
● Expertise with unit testing & Test-Driven Development (TDD)
● Experience on Cloud or AWS is preferable
● Have a good understanding and ability to develop software, prototypes, or proofs of
concepts (POC's) for various Data Engineering requirements.

Similar jobs (10)
4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms
∙Strong knowledge of data engineering, architecture and data modeling
∙Experience in platforms like Databricks and Snowflake
∙Experience on building applications on cloud (AWS or Azure or Google Cloud)
∙Strong analytical and problem-solving skills
∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an
advantage
∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional
Programming
∙Willingness to understand and enhance other people’s code, being able to work in an environment where
developers will oversee and work on wider components also dealing with older “legacy” code
∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not
already mastered at a sufficient level is important
∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house
developed frameworks is a must
∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile
methodology is an advantage
∙Prior knowledge of financial products is an advantage
∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage
Description
We are looking for Senior Data Engineers to join our AdTech team and build scalable, high-performance data platforms that power advertising insights and analytics. The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Spark and Scala.
You will work on designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
- Build and optimize distributed data applications using Spark and Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Work with large datasets to ensure data quality, consistency, and performance.
- Collaborate with engineering, product, and analytics teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, and cost efficiency.
- Deploy and manage data workloads in cloud and containerized environments.
- Troubleshoot production issues and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering or Big Data Engineering.
- Strong hands-on experience with Apache Spark and Scala.
- Experience building and maintaining ETL pipelines.
- Familiarity with Google Cloud Storage (GCS).
- Experience with Kubernetes (K8s).
- Strong SQL skills and understanding of distributed data processing.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with AWS and cloud-native data services.
- Familiarity with streaming technologies such as Kafka.
- Experience working on large-scale data platforms or AdTech systems.
- Exposure to orchestration tools such as Airflow.
Benefits
- Best-in-class salary: We hire strong talent and compensate accordingly.
- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
- High-impact work: Build AI-first systems and products used at scale by global clients.
About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
Company Name – Wissen Technology
Group of companies in India – Wissen Technology & Wissen Infotech
Work Location – Whitefield, Bangalore
Website and Company profile:
www.wissen.com
LinkedIn Page:
https://www.linkedin.com/company/wissen-technology/
While you may already know about Wissen and the company history, here is a quick rundown for you.
About Wissen Technology:
· The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.
· Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.
· Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.
· Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.
· Globally present with offices US, India, UK, Australia, Mexico, and Canada.
· We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
· Wissen Technology has been certified as a Great Place to Work®.
· Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.
· Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.
· We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.
About Role :
Key Responsibilities
- Build and maintain data transformation pipelines using java Spark
- Develop and optimize large-scale/CPU intensive data processing using Apache Spark
- Orchestrate workflows using Airflow
- Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage
- Support schema evolution, backfills, and incremental processing
- Ensure pipelines meet SLAs for freshness, reliability, and performance
- Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)
Required Skills & Qualifications
- Strong hands-on experience with
- HBase
- Apache Spark
- Experience with HBase or similar lakehouse query engines
- Airflow
- Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)
- Proficiency in Java
- Experience with Git-based development and CI/CD
Nice-to-Have Skills
- OpenTable format/Iceberg ,Apache Arrow
- CDC-based analytics pipelines
- Cloud platforms (AWS)
- Kubernetes-based data platforms
Job Title : Senior Data Engineer – Databricks
Experience : 14 to 20 Years
Location : HSR Layout, Bangalore
Work Mode : Hybrid – 3 Days WFO
Shift : 11:30 AM – 07:30 PM IST
Positions : 2
Notice Period : Immediate Joiners Only
Interview : 1 Technical Round + 2 Client Rounds
Role Overview :
We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.
The role requires a strong hands-on Data Engineering professional with expertise in Databricks, PySpark, Python, SQL, and AWS, along with technical leadership and stakeholder management experience.
Must-Have Skills :
- 14 to 20 years of Data Engineering experience
- Databricks & Apache Spark / PySpark
- Python & SQL
- AWS Cloud
- Lakehouse Architecture
- ETL / ELT & Distributed Data Processing
- Batch & Streaming Pipelines
- Data Pipeline Optimization & Data Modeling
- CDC & Incremental Processing
- Git, CI/CD & Testing
- Data Quality, Monitoring & Observability
- Technical Leadership & Stakeholder Management
Key Responsibilities :
- Design and build scalable data pipelines using Databricks, PySpark, Python, SQL, and AWS.
- Own data products from design through production.
- Develop batch / streaming pipelines and reusable ETL / ELT frameworks.
- Optimize pipelines for performance, scalability, reliability, and cost.
- Design scalable data architectures and data models.
- Implement data quality, monitoring, lineage, and CI/CD practices.
- Lead technical discussions and mentor engineering teams.
- Collaborate with business stakeholders, architects, product owners, and engineering teams.
- Remain hands-on while providing technical leadership.
Ideal Candidate :
A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.
🔴 Super Urgent : Only Bangalore-based immediate joiners.
Strong Tech Lead / Staff Engineer / Lead Engineer Profiles
2
Mandatory (Experience 1) - Must have minimum 6+ years of overall Software Engineering/Development experience building production backend systems.
3
Mandatory (Experience 2) - Must have Tech Lead ownership, with experience setting technical direction, architecture, frameworks, or engineering standards used by other engineers.
4
Mandatory (Experience 3) - Must have strong hands-on Backend development experience with deep proficiency in at least one backend programming language. (Python, Java, Golang etc)
5
Mandatory (Experience 4) - Must have strong System design/distributed systems experience, including architectural trade-offs, scalability, failure modes, reliability, and long-term maintainability.
6
Mandatory (Experience 5) - Must have strong CS fundamentals in Data Structures & Algorithms, Operating Systems, and Networking, with the ability to apply them to complex backend/system problems
7
Mandatory (Experience 6) - Must have owned complex, ambiguous, or business-critical engineering problems end-to-end, demonstrating clear technical judgment, trade-offs, problem-solving, and measurable technical/business impact; not limited to feature implementation.
8
Mandatory (Experience 7) - Must have formal technical leadership experience, including mentoring Senior Engineers, conducting design/code reviews, driving engineering quality, and leading technical decisions across a team.
9
Mandatory (Experience 8) - Must be a hands-on IC + Tech Lead, with approximately 70–80% hands-on coding/engineering involvement, not a pure people-management profile.
10
Mandatory (Company) - Product Companies / Startups / B2B SaaS
11
Mandatory (Education) - CS degree or equivalent (B.Tech/B.E./B.S.)
12
Preferred (Skills) - Experience with Kafka/NATS/RabbitMQ, AWS, Docker/Kubernetes, CI/CD, observability, security/compliance, multi-tenant systems, and financial/billing platforms.
Company Description
TECHSOPHY specializes in productizing solutions based on new technology, focusing on emerging platforms of BPM & ECM, Low Code, AI (ML/RPA/NLP). Founded in 2009, TECHSOPHY operates with headquarters in California, USA, and regional offices in Dubai, UAE, and an offshore innovation center in Hyderabad, India.
Qualifications
- Solid Fundamentals and exceptional problem-solving skills
- Solid and fluent understanding of algorithms and data structures
- Proficiency in Scala + Spark
- Proficiency in Scala + Play framework
- Experience Range: 4 to 7 Years
Requirement:
Some or all of them – because we believe intelligent people can pick up whatever they need in a short period of time. You just need to prove that you can:
- Excellent programming skills and knowledge of Java / Scala
- Excellent software design, problem-solving, and debugging skills
- Experience with modern Big Data technologies such as Spark, NoSQL, Cassandra, Kafka, MapReduce, and the Hadoop ecosystem is a must-have
- Experience with data analytics and the ability to mine data to obtain insights are much appreciated
About AuxoAI:
AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data. What We Do We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions.
We help our clients with accelerating their digital and AI journeys through:
• AI Application Development
• Data, Digital and Cloud acceleration using AI
• AI Native Product Engineering
We are seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have 6+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.
Responsibilities:
* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.
* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.
* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.
* Implement data governance and security best practices to ensure compliance and data integrity.
* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.
* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.
Requirements :
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.
* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.
* Strong programming skills in languages such as Python, Java, or Scala.
* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.
* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.
Job Description:
Position: Lead / Senior Data Engineer
Location: Chennai
Shift: US Eastern Time ( 5:00 PM – 2:00 AM )
Experience : 8+ years
Notice Period: Immediate Joiner only
Roles and Responsibilities:
Role Overview
The Lead Data Engineer will be responsible for designing, developing, and delivering high-quality software and data solutions while leading a team of engineers. The role involves hands-on technical work, architectural decision-making, mentoring junior developers, and collaborating with cross-functional teams to ensure successful delivery of scalable data platforms and analytical solutions.
Key Responsibilities:
Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.
Define technical strategy, architecture, and best practices for development and data engineering.
Design and build optimized data pipelines using cutting-edge technologies in a cloud environment.
Construct infrastructure for efficient ETL processes from various sources and storage systems.
Architect, design, and maintain database pipeline architectures, ensuring readiness for AI/ML transformations.
Lead the implementation of algorithms and prototypes to transform raw data into useful information.
Review code for quality, scalability, and performance.
Collaborate with Product Managers, Business Managers, Designers, and QA teams to translate business requirements into technical solutions.
Develop analytical tools, programs, and reporting mechanisms.
Create data validation methods and data analysis tools.
Interpret data trends and patterns to establish operational alerts.
Conduct complex data analysis and present results effectively.
Prepare data for prescriptive and predictive modeling.
Ensure compliance with data governance and security policies.
Troubleshoot, debug, and resolve complex technical issues.
Drive continuous improvement in software and data development processes, tools, and methodologies.
Mentor and guide engineers through code reviews, technical discussions, and training.
Ensure timely delivery of projects while maintaining high engineering standards.
Continuously explore opportunities to enhance data quality and reliability.
Apply strong programming and problem-solving skills to develop scalable solutions.
Demonstrate passion for testing strategy, problem-solving, and continuous learning.
Willingness to acquire new skills and knowledge.
Possess a product/engineering mindset to drive impactful data solutions.
Experience working in distributed environments with global teams.
Stay current with emerging technologies and industry trends to propose innovative solutions.
Technical Skills and Experience Requirements
Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.
High proficiency in Python, Scala, and Spark for applied large-scale data processing.
Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
Solid understanding of batch and streaming data processing techniques.
Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
Experience with RDBMS and OLAP databases such as MySQL and Snowflake.
Familiarity with Agile methodologies.
Obsession for service observability, instrumentation, monitoring, and alerting.
Knowledge or experience in architectural best practices for building data lakes.
Qualifications - Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
Data Engineer
Location: Bengaluru, India (Hybrid)
Employment Type: Full-time
Experience: 3-5 years
Role Overview
What We’re Looking For:
- Bachelor’s degree in Computer Science/Engineering or equivalent experience required.
- Experience designing and shipping cloud services products.
- Experience driving and managing technical and architectural dependencies on AWS Cloud.
- A firm understanding of system architecture, cloud computing, PaaS/SaaS design principles, S3, DynamoDB, RDS mandatory.
- Experience in building or maintaining ETL processes and tools, i.e., AWS Glue or any open-source tool.
- Proven system-level design contribution to a current “Live” (in production / under daily high load) multi-region SaaS or PaaS offering.
- Proven experience with S3, DynamoDB, SQL, and AWS RDS services.
- Proficiency in programming languages such as Python.
- Strong analytical and problem-solving skills.
Required Skills & Experience
- Experience with Python, SQL, and data visualization/exploration tools.
- Familiarity with the AWS ecosystem, specifically S3, DynamoDB, and RDS.
- Communication skills, especially for explaining technical concepts to nontechnical business leaders.
- Ability to work on a dynamic, research-oriented team that has concurrent projects.
- Experience in AWS cost optimization (Savings Plans, Reserved Instances, Spot Instances) and governance frameworks.
- Experience developing solutions using infrastructure orchestration tools (SSM, automation account, Ansible, etc.).
- Excellent leadership, stakeholder management, and communication skills.
What We Offer
- Work with some of the brightest minds in the emerging EV industry.
- Make a tangible impact in reducing carbon emissions and enabling sustainable energy.
- Freedom to suggest, implement, and innovate on systems, processes, and technologies.
- Daily ownership in a high-growth, challenging environment.
- Flexible work environment with hybrid schedules and virtualization options.
- Competitive pay and benefits including health coverage, innovative PTO program, and performance bonuses.







