Senior Data Engineer at Internshala · Gurugram · 3 - 5 years · ₹15L - ₹19L / yr · Bootstrapped · Posted 6 Mar 2023
Internshala is a dot com business with the heart of dot org.
We are a technology company on a mission to equip students with relevant skills & practical exposure through internships, fresher jobs, and online trainings. Imagine a world full of freedom and possibilities. A world where you can discover your passion and turn it into your career. A world where your practical skills matter more than your university degree. A world where you do not have to wait till 21 to taste your first work experience (and get a rude shock that it is nothing like you had imagined it to be). A world where you graduate fully assured, fully confident, and fully prepared to stake a claim on your place in the world.
At Internshala, we are making this dream a reality!
👩🏻💻 Your responsibilities would include-
- Designing, implementing, testing, deploying, and maintaining stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our central data warehouse, and moving data out to applications and affiliates
- Developing analytical tools and programs that can help in Analyzing and organizing raw data
- Evaluating business needs and objectives
- Conducting complex data analysis and report on results
- Collaborating with data scientists and architects on several projects
- Maintaining reliability of the system and being on-call for mission-critical systems
- Performing infrastructure cost analysis and optimization
- Generating architecture recommendations and the ability to implement them
- Designing, building, and maintaining data architecture and warehousing using AWS services.
- ETL optimization, designing, coding, and tuning big data processes using Apache Spark, R, Python, C#, and/or similar technologies.
- Disaster recovery planning and implementation when it comes to ETL and data-related services
- Define actionable KPIs and configure monitoring/alerting
🍒 You will get-
- A chance to build and lead an awesome team working on one of the best recruitment and online trainings products in the world that impact millions of lives for the better
- Awesome colleagues & a great work environment
- Loads of autonomy and freedom in your work
💯 You fit the bill if-
- You have the zeal to build something from scratch
- You have experience in Data engineering and infrastructure work for analytical and machine learning processes.
- You have experience in a Linux environment and familiarity with writing shell scripts using Python or any other scripting language
- You have 3-5 years of experience as a Data Engineer or similar software engineering role

About Internshala
About
Internshala is six years old and on its way to solving a problem that is at least 50 years old - the problem of meaningful internships. Millions of students, just like you, struggle to find an internship every year - we are changing that.
Imagine a world full of freedom and possibilities. A world where you can discover your passion and turn it into your career. A world where your practical skills matter more than your university degree. A world where you do not have to wait till 21 to taste your first work experience (and get a rude shock that it is nothing like you had imagined it to be). A world where you graduate fully assured, fully confident, and fully prepared to stake the claim on your place in the world. At Internshala, we are making this dream a reality. Join us!
Wondering what it is like to work at Internshala? Catch a glimpse of Internshala work culture at https://internshala.com/culture
Connect with the team
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Job Title : Data / AI / GenAI – Engineering & Analytics
Experience : 4+ Years
Location : Noida / Gurugram / Ahmedabad
Employment Type : Full-time | On-site at client location
Working Days : 5 days per week
Working Hours : Standard business hours
Position Overview : We are seeking professionals to deliver modern data engineering, business intelligence, cloud analytics and AI-powered applications, according to their specialization.
Mandatory Skills :
Python, SQL, ETL/ELT, Data Engineering, Power BI, Azure Data Factory, Databricks, PySpark, Data Modeling, GenAI/LLMs, RAG, Vector Databases, AI Agents (as per role specialization).
Key Roles / Specializations :
- Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
- Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
- Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
- Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
- GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
- Agentic AI Engineers : AI agents, tool calling, orchestration and multi-agent workflows
Key Responsibilities :
- Design, develop and maintain data pipelines, analytics solutions or AI applications.
- Build and optimize data integration, transformation and processing workflows.
- Develop dashboards and analytical models for business decision-making.
- Use cloud data platforms and modern engineering frameworks.
- Develop and evaluate LLM applications, RAG solutions or AI agents as applicable.
- Ensure data quality, security, performance and reliability.
- Collaborate with engineering teams and stakeholders on testing, deployment and documentation.
Required Skills & Qualifications :
- Bachelor’s degree in Computer Science, IT, Data Science, Engineering or related discipline.
- 4–5 years of relevant experience in data, analytics, AI or software engineering.
- Hands-on expertise in at least one listed specialization; not all technologies are required.
- Relevant Python, SQL, DAX or other technical skills depending on the position.
- Understanding of cloud platforms, APIs, integration and software practices.
Preferred Qualifications :
- Azure, Databricks or Microsoft Fabric experience.
- For GenAI roles : Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex or LangGraph.
- For relevant roles : vector databases, CI/CD, Docker, MLOps or LLMOps.
Note : Candidates are expected to have expertise in their relevant specialization, not in every listed technology or role.
Job Summary
Role Overview
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops
Job Description
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Develop data processing solutions using Python.
- Write complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain data ingestion and integration workflows.
- Implement data quality, validation, monitoring, and error-handling processes.
- Develop and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
- Collaborate with data analysts, data scientists, software engineers, and business teams.
- Optimize data pipelines for performance, reliability, and scalability.
- Troubleshoot production data issues and ensure timely resolution.
- Follow best practices for version control, code quality, testing, and deployment.
Mandatory Skills
- Python
- ETL
- SQL
- CI/CD
- DevOps
- Git / Version Control
- Strong problem-solving and debugging skills
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.
About Us
We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable.
Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.
We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life.
Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk.
Our Guiding Principles
These principles define how we work at Incubyte. They are non-negotiable.
Relentless Pursuit of Quality with Pragmatism
We build high-quality systems without losing sight of delivery.
Extreme Ownership
We take responsibility end-to-end for decisions, execution, and outcomes.
Proactive Collaboration
We collaborate closely, challenge each other, and solve problems together.
Active Pursuit of Mastery
We continuously improve our craft and raise our bar.
Invite, Give, and Act on Feedback
We seek, give, and act on feedback to get better every day.
Ensuring Client Success
We act as trusted partners and focus on real outcomes, not just output.
Job Description
This is a remote position.
Experience Level
2+ years of experience in SQL, Python, and Snowflake (or equivalent cloud data warehouse), Azure Cloud services.
Role Overview
If you're a Data Craftsperson who takes pride in clean, well-tested data solutions and believes in the principles of Extreme Programming, we'd love to meet you. At Incubyte, we're a DevOps organization where developers own the entire release cycle — you'll get hands-on experience across data engineering, analytics, cloud infrastructure, and direct client communication. This role sits primarily in data engineering (80%) with a meaningful analytics component (20%), supporting our client's data systems end-to-end.
What You'll Do
- Design, build, and maintain data pipelines and infrastructure using SQL and Python
- Work within Snowflake to build and optimize data models supporting business use cases
- Parse and process structured and semi-structured data (JSON, XML) from varied sources
- Diagnose issues across raw, intermediate, and summary tables
- Build SQL queries to support repeatable analytics use cases based on stakeholder requirements
- Investigate and resolve data quality issues, including time-sensitive or urgent ones
- Identify opportunities to consolidate models and maintain a single source of truth (SSOT)
Requirements
What We're Looking For
- 2+ years of experience with SQL and relational databases, with the ability to understand complex data relationships and transformations (required)
- 2+ years of experience with Python for data engineering tasks (required)
- Experience with Snowflake or an equivalent cloud data warehouse (required)
- Experience working with Snowflake Coco or any other AI tools(required)
- Experience parsing JSON and XML data (a plus)
- A strong eye for data quality and attention to detail
- Knowledge of Git (required)
- Knowledge of Azure cloud services such as Azure Data Factory, Azure Blob Storage, and Azure SQL Database (required)
- Knowledge of data infrastructure/modeling tools like DBT, Fivetran (a plus)
- Experience with BI tools like Power BI(a plus, not core to this role)
- Knowledge of Docker, Linux, Shell/Bash, and virtualization technologies (a plus)
- Knowledge of SSIS packages (a plus)
- Familiarity with CI/CD methodologies
Benefits
Life at Incubyte
We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered.
Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion.
Perks
- Dedicated learning & development budget.
- Sponsorship for conference talks.
- Comprehensive medical & term insurance.
- Employee-friendly leave policies.
- Home Office fund
- Medical Insurance
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
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!
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.
Strong Data Engineer (AWS) Profile
2
Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.
3
Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.
4
Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.
5
Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.
6
Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.
7
Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.
8
Mandatory (Education) – B.Tech / B.E./ M.Tech
Job Description – Data / Metadata Engineer
Position
Data / Metadata Engineer
Location
Pune
Experience
- 6–9 Years: Up to 28 LPA
- 10–17 Years: Up to 32 LPA
Notice Period
Immediate to 15 Days Joiners Preferred
Role Overview
We are looking for an experienced Data / Metadata Engineer with strong expertise in Data Engineering, Metadata Management, Data Modeling, Cloud technologies, Python/PySpark, and ETL/Data Pipelines.
The ideal candidate should have hands-on experience designing and developing data solutions, working with metadata and data models, and building scalable data pipelines on cloud platforms.
Mandatory Skills
- Strong experience in Data Engineering
- Hands-on experience in Metadata Management / Metadata Engineering
- Strong understanding of Data Modeling
- Experience with DDL and ER/Data Modeling
- Experience with Cloud technologies – Any Cloud Platform
- Strong programming experience in Python or PySpark
- Experience with ETL processes and Data Pipelines
- Good understanding of data architecture and data integration concepts
Key Responsibilities
- Design, develop, and maintain scalable data engineering solutions.
- Develop and manage data pipelines and ETL workflows.
- Work with metadata and data cataloging concepts.
- Create and maintain data models, DDLs, ER diagrams, and database structures.
- Develop data processing solutions using Python or PySpark.
- Work with cloud-based data platforms and services.
- Collaborate with Data Architects, Data Engineers, Developers, and Business teams.
- Ensure data quality, consistency, availability, and reliability across data pipelines.
- Troubleshoot and optimize existing data pipelines and data processes.
- Follow best practices for data engineering, modeling, and cloud-based implementations.
Candidate Profile
- Strong experience in Data Engineering + Metadata + Data Modeling.
- Good hands-on experience with Python/PySpark and ETL/Data Pipelines.
- Experience working with any major cloud platform.
- Strong understanding of databases, data structures, and data modeling concepts.
- Candidates who can join immediately or within 15 days are preferred.
Job Details
Role: Data / Metadata Engineer
Location: Pune
Experience: 6–17 Years
Budget: 28 LPA (6–9 Yrs) / 32 LPA (10–17 Yrs)
Notice Period: Immediate to 15 Days














