Principal Data Engineer

Strong Data Engineer (AWS) Profile

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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.

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Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

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Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

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Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

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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.

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Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

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Mandatory (Education) – B.Tech / B.E./ M.Tech

1. Company Description:

Tatvic, is a marketing analytics company focusing on generating insights from data using long association with Google & its infrastructure. We breed,recognize and reward performance. As a company we are growing very fast & we are under transformation. To enable this transformation we need future leaders with eyesight which balances execution & strategic understanding.

Website: www.tatvic.com

2. Role Details

• Role: Lead Data Engineer
• Band: L4
• Department: Data Engineering
• Reporting to: L5 / Head of Delivery
• Location: Ahmedabad
• Job Type: Full Time
• Experience: 6-8 years of relevant experience
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.

3. Mission & Role Overview

• Mission: To create high-level organizational impact by leading a team to design and deliver scalable, high-performance cloud-native data solutions. The Lead Data Engineer (L4) is responsible for ensuring technical excellence—specifically in BigQuery optimization and secure GCP/AWS architectures—while driving the transition to Agentic AI workflows and creating value through the development of L1-L3 engineers.
• Role Overview: This is a pivotal leadership role on the Management Track, responsible for end-to-end data outcomes for the function. The Lead Engineer ensures the quality of engineering execution, manages team utilization and resource allocation, and serves as the primary technical representative in cross-functional forums with Marketing, Strategy, and Product teams.

4. Key Responsibilities

• Lead the design, development, and deployment of scalable and efficient cloud-based data pipelines and architectures.
• Build reusable data solutions and software components that serve multiple customers and use cases.
• Architect cloud environments using GCP, ensuring best practices in IAM, Security, and Networking.
• Conduct Exploratory Data Analysis (EDA) on clickstream and behavioral datasets to derive insights.
• Manage end-to-end ETL processes, including data extraction, transformation, and loading using Python, SQL, and Airflow.
• Design and build production-grade software (APIs, services, internal tools) with sound engineering practices — version control, testing, CI/CD, and code review.
• Extend data platforms with AI capabilities — integrating LLMs, RAG pipelines, and agentic workflows where they add clear business value.
• Perform Root Cause Analysis (RCA) and resolve data quality, pipeline, or application issues.
• Collaborate cross-functionally with Marketing, Insights, Product, and Engineering teams to align data initiatives with business goals.
• Document architectures, design decisions, and operations clearly and consistently.
• Coach and mentor team members, ensuring technical excellence and continuous learning.
• Participate in recruitment and knowledge-sharing through interviews, blogs, and webinars.

5. Must-Have & Good-to-Have Skills

Must-Have Skills:

• Strong understanding of clickstream data and data pipeline architecture
• Hands-on experience with cloud platforms (GCP)
• Expertise in SQL, Python, and Airflow
• Solid software engineering foundation — API design, testing, version control, and deployment practices
• Proven ability to perform exploratory data analysis and data validation
• Knowledge of cloud security, IAM, and networking best practices
• Working knowledge of building or integrating AI/LLM-based components into existing systems
• Excellent problem-solving, stakeholder management, and communication skills

Good-to-Have Skills:

• Certifications such as: Google Cloud Professional Data Engineer / Cloud Architect
• AWS Certified Data Analytics or Azure Data Engineer Associate
• Google Analytics 4 (GAIQ)
• Experience in marketing attribution, commerce data, or analytics ecosystems
• Exposure to cost optimization and cloud resource management
• Experience with agent frameworks (LangChain, ADK, MCP) or LLM APIs
• Experience building automation frameworks or internal data tools

6. Not-a-Fit Criteria

• Individual Contributor Focus: Operates as the team's best individual contributor instead of building team capability or empowering L3s.
• Information Hoarding: Keeps architectural patterns or tribal knowledge trapped in their head rather than creating reusable playbooks and documentation.
• Avoidance of Conflict: Avoids difficult performance conversations with underperforming team members, allowing capability gaps to persist.
• Activity Over Outcomes: Measures success by "tasks completed" rather than pipeline stability, data accuracy, or business impact.
• Functional Siloing: Fails to build partnerships with Marketing or Product teams, leading to misaligned data delivery.

Our Culture & Perks - Where Passion Meets Purpose:

• Competitive CTC: Based on experience and skillset
• Medical Insurance for you and your family
• Return-to-Work Program for New Moms — because career breaks shouldn’t break momentum
• 1 Work From Home Day/Month — flexibility when life calls
• 2 Birthday Leaves/Year — one for you, one for someone you love
• Monthly Engagement Activities — from game nights to learning sessions
• Inclusive Culture & Equal Opportunity Employer — diversity drives our innovation
• We Think Like Engineers & Athletes: we build, we iterate, we scale, we win — together
• 5-day workweek — because balance drives brilliance

We are hiring experienced Data Engineers for a permanent opportunity in Bangalore.

Job Description

Role: Data Engineer

Location: Bangalore

Experience: 6+ Years

Key Responsibilities:

• Design, develop, and maintain scalable data processing pipelines using Amazon EMR.
• Develop data engineering solutions using Python and Scala.
• Process and transform large volumes of structured and unstructured data.
• Build and optimize distributed data processing workflows for performance and scalability.
• Work with big data technologies and cloud-based data processing environments.
• Perform data integration, validation, transformation, and quality checks.
• 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.

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

SHARE YOUR RESUME : { pavithra.e @vysystems.com },

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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

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.

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

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!

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 :

1. Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
2. Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
3. Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
4. Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
5. GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
6. 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.

1st virtual , 2nd round F2F

Python pyspark, SQL, data engineer

5+yrs

9+yrs

Bangalore/Hyderabad

immediate to 15days.