Snowflake, DBT

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

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

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.

Sr. Data Engineer 

Location: Pune

Responsibilities 

· Lead the end-to-end design and development of scalable, high-performance data pipelines and ETL/ELT frameworks aligned with modern data engineering best practices. 

· Architect complex data integration workflows that bring together structured, semi-structured, and unstructured data from both cloud and on-premise sources. 

· Build robust real-time, batch, and on-demand pipelines with built-in observability—monitoring, alerting, and automated error handling. 

· Partner with analysts, data scientists, and business leaders to define and deliver reliable data models, quality frameworks, and SLAs that power key business insights. 

· Ensure optimal pipeline performance and throughput, with clearly defined SLAs and proactive alerting for data delivery or quality issues. 

· Collaborate with platform, DevOps, and architecture teams to build secure, reusable, and CI/CD-enabled data workflows that align with enterprise architecture standards. 

· Establish and enforce the best practices in source control, code reviews, testing automation, and continuous delivery for all data engineering components. 

· Lead root cause analysis (RCA) and preventive maintenance for critical data failures, ensuring minimal business impact and continuous service improvement. 

· Guide the team in establishing standards for data modeling, transformation logic, and governance, ensuring long-term maintainability and scalability. 

· Design and execute comprehensive testing strategies—unit, integration, and system testing—ensuring high data reliability and pipeline resilience. 

· Monitor and fine-tune data pipeline and query performance, optimizing for reliability, scalability, and cost-efficiency. 

· Create and maintain detailed technical documentation, including data architecture diagrams, process flows, and integration specifications for internal and external stakeholders. 

· Facilitate and lead discussions with business and operational teams to understand data requirements, prioritize initiatives, and drive data strategy forward. 

Qualifications 

· 7 to 10 years of hands-on experience in data engineering roles with a proven record of building scalable and secure data platforms. 

· Over 5 years of experience in scripting languages such as Python for data processing, automation, and ETL development. 

· 4+ years of experience with Snowflake, including performance tuning, security model design, and advanced SQL development. 

· 5+ years of experience with data integration tools such as Azure Data Factory, Fivetran, or Matillion. 

· 5+ years of experience in writing complex, highly optimized SQL queries on large datasets. 

· Proven experience integrating and managing APIs, JSON, XML, and webhooks for data acquisition. 

· Hands-on experience with cloud platforms (Azure/AWS) and orchestration tools like Apache Airflow or equivalent. 

· Experience with CI/CD pipelines, automated testing, and code versioning tools (e.g., Git). 

· Familiarity with dbt or similar transformation tools and best practices for modular transformation development. 

· Exposure to data visualization tools like Power BI for supporting downstream analytics is a plus. 

· Strong interpersonal and communication skills with the ability to lead discussions with technical and business stakeholders. 

Education 

Bachelor’s or Master’s degree in Computer Science/Information technology or related field. 

Equivalent academic and work experience can be considered. 

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.

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.

Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration

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.

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  

Data Engineer – Microsoft Fabric

Location: Pune, India

Work Mode: Hybrid

Experience: 6+ Years

Employment Type: Full-time contactor

Compensation: As per market standards, commensurate with experience and expertise

Shift Timings: 2:00 PM – 11:00 PM IST

Notice Period: 0 – 15 days

About the Role

Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.

We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.

The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.

Roles and Responsibilities

• Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
• Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
• Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
• Implement Medallion Architecture using Bronze, Silver and Gold layers.
• Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
• Develop and maintain data models, tables, views and optimized SQL queries.
• Build and support semantic models for Power BI and analytical workloads.
• Implement data quality, validation, monitoring and error-handling mechanisms.
• Work with metadata, lineage and governance requirements using Microsoft Purview.
• Implement data security, access controls and role-based permissions across data platforms.
• Support Data Product and domain-oriented data architecture principles.
• Follow DataOps practices including CI/CD, deployment, monitoring and production support.
• Troubleshoot pipeline failures, performance issues and data quality problems.
• Optimize data pipelines, queries and storage for performance and cost efficiency.
• Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
• Participate in technical design discussions, code reviews and architecture reviews.
• Maintain technical documentation, data flow diagrams and pipeline documentation.
• Support production deployments, incident resolution and SLA-driven data platform operations.
• Identify opportunities for automation and AI-assisted improvements across data engineering processes.

Qualifications and Skills

• 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
• Strong hands-on experience with Microsoft Fabric.
• Experience with:
• Microsoft Fabric Lakehouse
• Fabric Warehouse
• OneLake
• Fabric Data Factory / Pipelines
• Semantic Models
• Strong understanding of Lakehouse and Medallion Architecture.
• Strong SQL development and query optimization skills.
• Hands-on experience with Python and/or PySpark.
• Experience developing enterprise ETL/ELT and data integration pipelines.
• Experience with batch and incremental data processing.
• Understanding of data modelling concepts including dimensional modelling.
• Knowledge of data quality, metadata, lineage and data governance.
• Working knowledge of Microsoft Purview.
• Understanding of Data Mesh and Data Product concepts.
• Experience with CI/CD, version control, monitoring and DataOps practices.
• Understanding of cloud security, access controls and data privacy.
• Good troubleshooting and problem-solving skills.
• Strong communication skills and ability to work with distributed and client-facing teams.

Preferred Skills

• Microsoft Fabric or Azure Data certifications.
• Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
• Experience implementing Medallion Architecture on Microsoft Fabric.
• Experience with Power BI and semantic modelling.
• Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
• Experience working with Data Products or domain-oriented data solutions.
• Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
• Experience working with US or international enterprise clients.

What We Expect

The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.