Data Scientist

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

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

This role will be permanent with NAM info and deploy to client location Hyderabad & Pune.

Work Mode: WORK FROM OFFICE

Role Descriptions:

• Perform detailed data analysis and support business decision-making
• Gather and document business requirements and translate them into technical specifications
• Work closely with stakeholders to define data needs and reporting requirements
• Create user stories, functional specifications, and support UAT activities
• Ensure alignment between business objectives and data solutions

Required Skills:

• Strong expertise in SQL and data querying
• Proven experience in data analysis, requirement gathering, and stakeholder management
• Ability to translate business requirements into technical solutions and user stories
• Good understanding of data models, reporting, and analytics concepts

Skills: Business Analysis~ORACLE SQL

Locations: ~HYDERABAD~PUNE~

Desire candidate

• Candidate should have valid PF.

About VerbaFlo.ai:

VerbaFlo.ai is a fast-growing AI SaaS startup revolutionizing how businesses leverage AI-powered solutions. As a part of our dynamic team, you’ll work alongside industry leaders and visionaries to drive innovation and execution across multiple functions.

Role Overview:

We are seeking a Senior Business Data Analyst with strong experience in analytics, SQL, and dashboarding (preferably Metabase) who can independently lead complex analytical initiatives, translate business problems into scalable data solutions, and mentor junior analysts. This role demands someone who can think strategically, operate with high ownership, and ensure the company runs on accurate, timely, and actionable insights.

Responsibilities:

Strategic & Cross-Functional Ownership

• Partner with leadership (Product, Ops, Growth, Finance) to translate business goals into analytical frameworks, KPIs, and measurable outcomes.
• Influence strategic decisions by providing data-driven recommendations, forecasting, and scenario modeling.
• Drive adoption of data-first practices across teams and proactively identify high-impact opportunity areas.

Analytics & Dashboarding

• Own end-to-end development of dashboards and analytics systems in Metabase (or similar BI tools).
• Build scalable KPI frameworks, business reports, and automated insights to support day-to-day and long-term decision-making.
• Ensure data availability, accuracy, and reliability across reporting layers.

Advanced Data Analysis

• Write, optimize, and review complex SQL queries for deep-dives, cohort analysis, funnel performance, and product/operations diagnostics.
• Conduct root-cause analysis, hypothesis testing, and generate actionable insights with clear recommendations.

Data Infrastructure Collaboration

• Work closely with engineering/data teams to define data requirements, improve data models, and support robust pipelines.
• Identify data quality issues, define fixes, and ensure consistency across systems and sources.

Leadership & Process Excellence

• Mentor junior analysts, review their work, and establish best practices across analytics.
• Standardize reporting processes, create documentation, and improve analytical efficiency.

Core Requirements:

• 5–8 years of experience as a Business Analyst, Data Analyst, Product Analyst, or similar role in a fast-paced environment.
• Strong proficiency in SQL, relational databases, and building scalable dashboards (Metabase preferred)
• Demonstrated experience in converting raw data into structured analysis, insights, and business recommendations.
• Strong understanding of product funnels, operational metrics, and business workflows.
• Ability to communicate complex analytical findings to both technical and non-technical stakeholders.
• Proven track record of independently driving cross-functional initiatives from problem definition to execution.
• Experience with Python, Git, or BI tools like Looker/Power BI/Tableau.
• Hands-on with data warehouses (BigQuery, Redshift, Snowflake).
• Familiarity with product analytics tools (Mixpanel, GA4, Amplitude).
• Exposure to forecasting, financial modeling, or experimentation (A/B testing).

Why Join Us?

• Work directly with top leadership in a high-impact role.
• Be part of an innovative and fast-growing AI startup.
• Opportunity to take ownership of key projects and drive efficiency.
• A collaborative, ambitious, and fast-paced work environment.
• Perks & Benefits: gym membership benefit, workation policy, and company-sponsored lunch.

If you’re looking for an exciting role that combines strategy, execution, and leadership exposure, we’d love to hear from you!

Apply now to join VerbaFlo.AI on this journey.

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

Job Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

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.

1st virtual , 2nd round F2F

Python pyspark, SQL, data engineer

5+yrs

Bang/hyderabad

immediate to 15days.

Immediate Joining

We are looking for a Dedicated Resource on Contract for –

Role: Data Engineer

Experience: 5+ Years

Location: Remote

Duration: 3+ Months

Strong hands-on experience with Snowflake, including writing SQL queries, creating views, stored procedures, and functions.

Good knowledge of AI tools such as Claude.

Experience with ETL tools like Alteryx is good to have.

Power BI experience is good to have.

Strong communication skills.