DATA ENGINEER at Wissen Technology · Bengaluru (Bangalore), Pune, Mumbai · 7 - 12 years · Profitable · Posted 13 Oct 2025

Wissen Technology is hiring for Data Engineer
About Wissen Technology:At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.
Job Summary:Wissen Technology is hiring a Data Engineer with a strong background in Python, data engineering, and workflow optimization. The ideal candidate will have experience with Delta Tables, Parquet, and be proficient in Pandas and PySpark.
Experience:7+ years
Location:Pune, Mumbai, Bangalore
Mode of Work:Hybrid
Key Responsibilities:
- Develop and maintain data pipelines using Python (Pandas, PySpark).
- Optimize data workflows and ensure efficient data processing.
- Work with Delta Tables and Parquet for data storage and management.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
- Ensure data quality and integrity throughout the data lifecycle.
- Implement best practices for data engineering and workflow optimization.
Qualifications and Required Skills:
- Proficiency in Python, specifically with Pandas and PySpark.
- Strong experience in data engineering and workflow optimization.
- Knowledge of Delta Tables and Parquet.
- Excellent problem-solving skills and attention to detail.
- Ability to work collaboratively in a team environment.
- Strong communication skills.
Good to Have Skills:
- Experience with Databricks.
- Knowledge of Apache Spark, DBT, and Airflow.
- Advanced Pandas optimizations.
- Familiarity with PyTest/DBT testing frameworks.
Wissen Sites:
- Website: http://www.wissen.com
- LinkedIn: https://www.linkedin.com/company/wissen-technology
- Wissen Leadership: https://www.wissen.com/company/leadership-team/
- Wissen Live: https://www.linkedin.com/company/wissen-technology/posts/feedView=All
- Wissen Thought Leadership: https://www.wissen.com/articles/
Wissen | Driving Digital Transformation
A technology consultancy that drives digital innovation by connecting strategy and execution, helping global clients to strengthen their core technology.

About Wissen Technology
About
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.
With offices in 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.
Leveraging our multi-site operations in the USA and India and availability of world-class infrastructure, we offer a combination of on-site, off-site and offshore service models. Our technical competencies, proactive management approach, proven methodologies, committed support and the ability to quickly react to urgent needs make us a valued partner for any kind of Digital Enablement Services, Managed Services, or Business Services.
We believe that the technology and thought leadership that we command in the industry is the direct result of the kind of people we have been able to attract, to form this organization (you are one of them!).
Our workforce consists of 1000+ highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like MIT, Wharton, IITs, IIMs, and BITS and with rich work experience in some of the biggest companies in the world.
Wissen Technology has been certified as a Great Place to Work®. The technology and thought leadership that the company commands in the industry is the direct result of the kind of people Wissen has been able to attract. Wissen is committed to providing them the best possible opportunities and careers, which extends to providing the best possible experience and value to our clients.
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Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
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.
About the Role
We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.
Key Responsibilities
- Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
- Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
- Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
- Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
- Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
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- Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
- Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
- Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
- Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
- Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
- Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
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- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
- Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.
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- Hands-on exposure to Microsoft Fabric for data integration and analytics.
- Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
- Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
- Domain expertise in financial services.
We are hiring experienced Data Engineers for a permanent opportunity in Bangalore.
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- Process and transform large volumes of structured and unstructured data.
- Build and optimize distributed data processing workflows for performance and scalability.
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- Troubleshoot data pipeline issues and optimize processing performance.
- Collaborate with data architects, analysts, and development teams to deliver reliable data solutions.
Required Skills:
- Strong hands-on experience with Amazon EMR.
- Proficiency in Python and Scala.
- Experience in big data processing and data pipeline development.
- Good understanding of distributed computing and data transformation techniques.
- Experience in performance tuning and troubleshooting data processing jobs.
- Strong analytical, problem-solving, and communication skills.









