Senior Data Engineer (ETL, Go, Databricks)

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.

About Us:

The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Job Summary:

We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.

As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.

Key Responsibilities:

• Design, develop, test, and maintain optimal data pipeline and ETL architectures.
• Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
• Prepare and optimize data for predictive and prescriptive modeling.
• Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
• Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
• Utilize big data tools and frameworks to optimize data acquisition and preparation.
• Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
• Develop and curate data models for analytics, dashboards, and reports.
• Conduct code reviews, maintain production-level code, and implement testing approaches.
• Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
• Drive innovation and implement efficient new approaches to data engineering tasks.

Must-Have Skills:

• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
• 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
• 3–5 years of experience designing and implementing data warehouse solutions.
• Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
• Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
• Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
• Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
• Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
• Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
• Strong problem-solving, communication, and collaboration skills.

Good-to-Have Skills:

• Experience in integrating ERP data into data lakes.
• Experience with traditional ETL tools (e.g., Talend, Pentaho).

Competencies:

• Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
• Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
• Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
• Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Application Details

Ready to make an impact? Apply today and become part of the QX Impact team!

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  

Senior Data Engineer – Ab Initio | GCP | Spark | Agentic AI

Location: Bangalore

Experience: 5+ Years

Role: Senior Data Engineer

Work Mode: Bangalore

Job Summary

We are looking for an experienced Senior Data Engineer with strong expertise in Ab Initio, GCP, Apache Spark, and Agentic AI. The ideal candidate will have hands-on experience designing and developing scalable data engineering solutions, building data pipelines, and working with modern cloud and AI technologies.

The candidate should be comfortable working across traditional enterprise data platforms and emerging Generative AI / Agentic AI solutions.

Key Responsibilities

• Design, develop, and maintain scalable and high-performance data pipelines using Ab Initio, Spark, and GCP services.
• Develop and optimize complex ETL/ELT workflows using Ab Initio.
• Build and maintain data processing solutions using Apache Spark / PySpark.
• Develop cloud-based data solutions on Google Cloud Platform (GCP).
• Work with GCP data services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or equivalent services.
• Perform data integration, transformation, cleansing, and validation.
• Optimize data pipelines for performance, scalability, reliability, and cost.
• Collaborate with data architects,
• 
  

About Solutionara

Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.

Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.

As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.

Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.

AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.

Role Overview

Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.

This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.

Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years

Key Responsibilities

Data Engineering

• Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
• Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
• Develop high-quality SQL and Python-based data processing solutions.
• Implement batch and incremental data-processing patterns.
• Develop reusable engineering components and frameworks.
• Support complex data migration and transformation activities.
• Perform source-to-target mapping and technical data analysis.
• Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.

Database & Platform Engineering

• Design and optimize relational database schemas and data structures.
• Analyze and improve SQL/query performance.
• Support indexing, partitioning, storage optimization, and database performance.
• Implement appropriate database security and access controls.
• Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
• Troubleshoot database and pipeline performance issues.
• Contribute to cloud data-platform configuration and optimization.

Data Quality

• Implement automated validation and data-quality controls.
• Develop reconciliation processes between source and target systems.
• Identify duplicate, incomplete, inconsistent, and invalid data.
• Implement cleansing, standardization, validation, and exception-management logic.
• Work with technical and business stakeholders to understand and implement business data rules.

Technical Delivery

• Convert technical designs into reliable production solutions.
• Participate in technical design and code reviews.
• Mentor junior/mid-level engineers.
• Support estimation and technical planning.
• Troubleshoot complex production and integration issues.
• Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
• Document technical designs, mappings, configurations, operational procedures, and engineering decisions.

Consulting & AI-Led Working

• Understand the business purpose behind assigned engineering requirements.
• Raise risks, assumptions, dependencies, and potential improvements proactively.
• Communicate effectively with client and internal stakeholders.
• Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
• Independently verify AI-generated code and recommendations before implementation.
• Identify opportunities for engineering automation and process improvement.

Required Qualifications

• 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
• Advanced SQL skills.
• Strong hands-on Python experience.
• Strong ETL/ELT development experience.
• Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
• Experience with data modeling and database design.
• Experience with AWS, Azure, or another major cloud platform.
• Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
• Experience with performance tuning and optimization.
• Experience with data validation and reconciliation.
• Strong troubleshooting and analytical skills.
• Ability to take ownership of engineering deliverables with limited supervision.

Preferred Qualifications

• Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
• Experience with manufacturing, retail, distribution, or consumer-goods data.
• Experience with CI/CD and infrastructure/platform engineering practices.
• Experience with API and event-driven integrations.
• Previous consulting or technology-services experience.

What Success Looks Like

• Pipelines and databases perform reliably at enterprise scale.
• Engineering solutions are maintainable, reusable, and well documented.
• Data issues are detected and addressed systematically.
• Junior engineers receive effective technical guidance.
• Problems are owned through resolution rather than simply escalated.
• Engineering decisions reflect both technical requirements and client business objectives.

About the Role

You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

Key Responsibilities

• Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
• Design and optimize data models for AI and machine learning workloads.
• Develop reliable data foundations for MLOps, governance, and data lineage.
• Integrate data from multiple sources into modern data platforms.
• Leverage Snowpark ML and Snowflake's native AI capabilities.
• Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

• 5+ years of hands-on experience with Snowflake.
• Strong proficiency in SQL and Python.
• Experience with AWS, Azure, or GCP.
• Knowledge of cloud storage services such as S3, ADLS, or GCS.
• Strong understanding of Dimensional Modeling and Data Vault.
• Experience with Scala or Java is a plus.

Tech Stack

• Data Warehouse: Snowflake
• Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
• Cloud: AWS, Azure, GCP
• Storage: S3, ADLS, GCS
• AI/ML: Snowpark ML, MLOps

Perks & Benefits

• Public Speaking & Communication Program
• Mentoring Program with Senior Support Leads
• 360° Progress Reviews
• Weekly Learning Sessions & Guilds
• Paid Certifications
• Hackathons & Innovation Days
• Recognition & Rewards Programs
• Team Socials & Annual Offsites
• Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

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

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.

Job Title : Senior Data Engineer – GCP & Apache Spark

Job Details :

• Number of Positions : 3
• Employment Type : Contract-to-Hire (C2H)
• Experience Required : 5 to 8 Years
• Location : Manyata Tech Park, Bengaluru
• Work Mode : Hybrid – 3 Days in Office per Week
• Preferred Notice Period : Immediate to 15–20 Days
• Project Duration : Initially 6–8 months, with a strong possibility of extension for long-term projects
• Relocation : Candidates from outside Bengaluru can apply if they are willing to relocate.

Role Overview :

We are looking for experienced Senior Data Engineers with strong expertise in Google Cloud Platform (GCP), Apache Spark, BigQuery, and SQL to design, develop, and maintain scalable data pipelines and distributed data processing solutions.

The ideal candidate should have hands-on experience with cloud-based data engineering, end-to-end pipeline architecture, system design, performance optimization, debugging, and CI/CD practices.

Mandatory skills :

Apache Spark (PySpark / Scala), SQL, GCP, BigQuery, GCP Dataproc, Data Pipelines, System Design, CI/CD, Debugging & Problem-Solving.

Key Responsibilities :

• Design, develop, and maintain scalable data pipelines using Apache Spark, PySpark, and/or Scala.
• Build and optimize batch and distributed data processing workflows on GCP.
• Work extensively with BigQuery for data transformation, validation, analytics, and query optimization.
• Develop and maintain data workflows using GCP services, including Dataproc, BigQuery, and Cloud Storage.
• Design end-to-end data pipeline architectures with a focus on scalability, reliability, and performance.
• Write and optimize complex SQL queries for large-scale datasets.
• Troubleshoot and resolve data processing issues, pipeline failures, and performance bottlenecks.
• Implement CI/CD practices for data engineering workflows, testing, and deployments.
• Monitor pipeline performance and identify opportunities for continuous improvement.
• Collaborate with cross-functional teams to understand requirements and deliver reliable data solutions.
• Participate in code reviews, testing, production deployments, and production support.

Mandatory Skills :

• Strong hands-on experience with Apache Spark, including PySpark and/or Scala.
• Strong SQL skills and experience working with large-scale datasets.
• Hands-on experience with Google Cloud Platform (GCP).
• Practical experience with BigQuery and data warehousing concepts.
• Working knowledge of GCP Dataproc.
• Strong understanding of data pipelines, end-to-end workflows, and system design.
• Practical experience with CI/CD and deployment processes.
• Excellent debugging, troubleshooting, and problem-solving skills.

Preferred Skills :

• Experience with Apache Airflow, Google Cloud Composer, or similar orchestration tools.
• Knowledge of Kafka or other streaming and messaging technologies.
• Proficiency in Python for data engineering and automation.
• Experience with Git-based development workflows.
• Knowledge of Linux/Unix environments and shell scripting.
• Familiarity with monitoring, logging, data quality, and governance practices.

Required Qualifications :

• 5 to 8 years of experience in Data Engineering, Big Data Engineering, or a related field.
• Proven experience developing and maintaining scalable data pipelines.
• Strong understanding of distributed data processing and cloud-based data architecture.
• Ability to troubleshoot complex technical issues and optimize pipeline performance.
• Strong communication, collaboration, and ownership skills.

Interview Process :

Round 1 : AI-Based Interview

• Candidates must complete the AI interview as soon as possible after receiving the invitation.

Round 2 : Virtual Interview Drive

• Interviews are planned for the upcoming drive; exact dates will be communicated separately.

Round 3 : Online Client Interview

• Shortlisted candidates will attend the online interview.
• Candidates must be available throughout the day on the scheduled interview date.

role: data engineer

Python pyspark, SQL, data engineer

5+yrs

Bangalore/Hyderabad

immediate to 15days.