Scala Developer at Information Solution Provider Company · Delhi, Gurugram, Noida, Ghaziabad, Faridabad · 2 - 7 years · ₹10L - ₹15L / yr · Posted 22 Feb 2022

Roles and Responsibilities
- Good Hands-on exp. in Spark
- Extensive exp. in Scala (IDE- Eclipse/IntelliJ)
- Working knowledge to create and work on Maven Project. Scala Maven Plugin. POM File
- Azure Data Factory, Azure Databricks

Similar jobs (10)
Company: Wissen Technology
Position: Databricks Engineer
Experience: 6-10 Years
Location: Bengaluru/Mumbai
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.
Key Responsibilities
- Design, develop, and maintain scalable data processing applications using Python, PySpark, and Spark.
- Develop and optimize data pipelines and workflows on Databricks.
- 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.
- Write clean, maintainable, scalable, and efficient code following established coding standards and best practices.
- Perform data analysis and implement appropriate data validation and quality checks.
- Monitor, troubleshoot, and optimize performance issues across data workflows and pipelines.
- Work with relational databases and develop efficient SQL queries for data extraction and transformation.
- Participate in code reviews, testing, deployment, and continuous improvement of data engineering solutions.
- Use Git/version control and follow established software development and deployment practices.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
- Proven experience as a Databricks Developer, Data Engineer, or similar role.
- Strong hands-on expertise in Apache Spark and PySpark.
- 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.
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.
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
Job Description:
We are seeking a skilled Senior Data Engineer with expertise in Databricks to join our dynamic data team. The ideal candidate will design, build, and maintain scalable data pipelines and architectures to support our organization's data-driven initiatives and leverage Databricks to process large-scale datasets, optimize data workflows, enable advanced analytics and machine learning, and integrate Power BI for data visualization and reporting.
Key Responsibilities
· 5-8 years of professional work experience in a relevant field
· Proficient in Microsoft Fabric platform, Azure Databricks, ADF, Delta Lake, SQL Data Warehouse, Unity Catalog.
· Good Experience on Microsoft Dynamics 365
· Experience/ prior knowledge on semi structure data and Structured Streaming, Azure synapse, data lake, data warehouse.
· Proficient in creating Azure Data Factory pipelines for ETL/ELT processing; copy activity, custom Azure development etc.
· Good knowledge of SQL and Python for data manipulation, transformation, and analysis
· Understand business requirements to set functional specifications for reporting applications
- Data Pipeline Development: Design, develop, and maintain robust, scalable data pipelines using Databricks, Apache Spark, and other cloud-based technologies.
- Data Integration: Ingest, transform, and integrate data from diverse sources, including APIs, databases, streaming platforms, and third-party systems, into Databricks for analytics and reporting.
- Power BI Integration: Develop and optimize data models and datasets in Databricks for use in Power BI, ensuring efficient data connections and high-quality visualizations.
- Performance Optimization: Optimize data workflows, API calls, and queries on Databricks and Power BI for performance, cost-efficiency, and scalability.
- Data Modeling: Build and maintain data models to support business requirements, ensuring data quality, consistency, and accessibility for analytics and reporting.
- Cloud Integration: Implement data solutions on cloud platforms (e.g., AWS, Azure, GCP) integrated with Databricks, Power BI, and API ecosystems.
- Security & Compliance: Implement data governance, security, and compliance best practices within Databricks, Power BI, and API environments.
- Technical Skills:
- Proficiency in Databricks, including Delta Lake, Spark SQL.
- Strong programming skills in Python, Scala, or Java.
- Experience with Apache Spark for big data processing.
- Knowledge of SQL for querying and transforming data.
- Proficiency in Power BI for creating data models, DAX queries, and interactive dashboards.
Preferred Qualifications
- Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).
Experience with real-time data processing and streaming
Responsibilities and JD
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.
Hiring for Data Engineer - Delivery Manager
Exp : 10 - 15 yrs
Edu : BE/B.Tech/MCA
Work Loation : Hyderabad
.Roles & Responsibilitie:
Own end-to-end delivery of data engineering programs ensuring alignment with business goals, timelines, and quality standards.
Drive execution across multiple data initiatives within Azure and Databricks environments.
Provide technical leadership in designing and implementing scalable data pipelines using Python, PySpark, and Spark.
Required Skills:
Strong experience with Databricks, PySpark, Python, and Spark.
Expertise in Azure Data Services including ADF, ADLS, and Synapse.
Proven experience in delivery management, stakeholder management, and Agile execution
We are hiring for a Data Engineer & Java scala for a full-time opportunity in Bangalore.
Experience: 4–10 Years
Must-Have Skills:
Java / Scala / Python, Data Engineering, Databricks / Snowflake, and Cloud (AWS / Azure / GCP).
We are looking for strong software engineers with hands-on experience in data platform development, scalable backend programming, data integration, and cloud technologies.
Experience in Banking, Capital Markets, Market Risk, or Regulatory Reporting will be an added advantage.
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 Description – Data Engineer
Role: Data Engineer
Experience: 9+ Years
Location: Bangalore / Hyderabad
Notice Period: Immediate to 15 Days
Interview Process: 1st Round – Virtual | 2nd Round – F2F
Mandatory Skills
- Python
- PySpark
- SQL
- Azure Data Engineering
Job Description
We are looking for an experienced Azure Data Engineer with 9+ years of experience and strong hands-on expertise in Python, PySpark, SQL, and Azure Data Engineering.
Key Responsibilities
- Develop and maintain scalable data engineering solutions using Azure.
- Build and optimize data processing pipelines using PySpark and Python.
- Write complex SQL queries for data extraction and transformation.
- Work with Azure data services and cloud-based data platforms.
- Perform data processing, transformation, and integration.
- Troubleshoot data pipeline and production issues.
- Collaborate with technical and business teams to deliver data solutions.
Preferred: Immediate to 15 Days joiners.










