Data Engineer at SaaS Company strive to make selling fun with our SaaS incen · Bengaluru (Bangalore) · 4 - 8 years · ₹20L - ₹25L / yr · Posted 28 Jun 2022

What is the role?
You will be responsible for developing and designing front-end web architecture, ensuring the responsiveness of applications, and working alongside graphic designers for web design features, among other duties. You will be responsible for the functional/technical track of the project
Key Responsibilities
- Develop and automate large-scale, high-performance data processing systems (batch and/or streaming).
- Build high-quality software engineering practices towards building data infrastructure and pipelines at scale.
- Lead data engineering projects to ensure pipelines are reliable, efficient, testable, & maintainable
- Optimize performance to meet high throughput and scale
What are we looking for?
- 4+ years of relevant industry experience.
- Working with data at the terabyte scale.
- Experience designing, building and operating robust distributed systems.
- Experience designing and deploying high throughput and low latency systems with reliable monitoring and logging practices.
- Building and leading teams.
- Working knowledge of relational databases like Postgresql/MySQL.
- Experience with Python / Spark / Kafka / Celery
- Experience working with OLTP and OLAP systems
- Excellent communication skills, both written and verbal.
- Experience working in cloud e.g., AWS, Azure or GCP
Whom will you work with?
You will work with a top-notch tech team, working closely with the architect and engineering head.
What can you look for?
A wholesome opportunity in a fast-paced environment that will enable you to juggle between concepts, yet maintain the quality of content, interact and share your ideas and have loads of learning while at work. Work with a team of highly talented young professionals and enjoy the benefits of being at this company
We are
We strive to make selling fun with our SaaS incentive gamification product. Company is the #1 gamification software that automates and digitizes Sales Contests and Commission Programs. With game-like elements, rewards, recognitions, and complete access to relevant information, Company turbocharges an entire salesforce. Company also empowers Sales Managers with easy-to-publish game templates, leaderboards, and analytics to help accelerate performances and sustain growth.
We are a fun and high-energy team, with people from diverse backgrounds - united under the passion of getting things done. Rest assured that you shall get complete autonomy in your tasks and ample opportunities to develop your strengths.
Way forward
If you find this role exciting and want to join us in Bangalore, India, then apply by clicking below. Provide your details and upload your resume. All received resumes will be screened, shortlisted candidates will be requested to join for a discussion and on mutual alignment and agreement, we will proceed with hiring.

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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.
1st virtual , 2nd round F2F
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9+yrs
Bangalore/Hyderabad
immediate to 15days.
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.
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- Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.
Required Skills
- 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.
- Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
- Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
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Nice to Have
- 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.
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- Domain expertise in financial services.
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
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developers will oversee and work on wider components also dealing with older “legacy” code
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role: data engineer
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Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
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.
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Position: Databricks Engineer
Experience: 6-10 Years
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Employment Type: Full-time
About Wissen Technology
Wissen Technology is a global technology services company focused on delivering innovative software engineering, data, and technology solutions to leading enterprises. The company works with clients across industries to build scalable, high-performance technology platforms and solve complex business and technology challenges.
With a strong focus on engineering excellence, innovation, and collaboration, Wissen Technology brings together skilled technology professionals across areas such as software engineering, data engineering, cloud, analytics, and digital transformation.
At Wissen Technology, employees have the opportunity to work on challenging technology projects, collaborate with experienced engineering teams, and contribute to solutions that create measurable business impact.
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- Design, develop, and maintain scalable data processing applications using Python, PySpark, and Spark.
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- Collaborate with data engineers, data scientists, business stakeholders, and other technical teams to understand requirements and deliver high-quality solutions.
- Ensure data integrity, quality, performance, and reliability across data processing pipelines.
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Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
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- Strong programming skills in Python; experience with Scala is an advantage.
- Strong proficiency in SQL and hands-on experience with relational databases.
- Practical experience developing and optimizing data pipelines and data processing applications.
- Familiarity with Git and version control systems.
- Strong understanding of data engineering concepts, data transformation, and data validation.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
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Job Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.









