Associate Data Forward Deployed Engineer at Zirodigital · Hyderabad · 0 - 2 years · ₹7L - ₹7L / yr · Posted 18 Oct 2026

Hiring: 10 openings for Associate Data Forward Deployed Engineer (0–2 yrs) for a fast-growing AI platforms & services company, Hyderabad (confidential client) via Ziro.digital.
Location: Hyderabad (onsite, full-time). Open to candidates from anywhere in India willing to relocate. Experience: 0–2 years. 2024/2025/2026 graduates welcome (B.Tech/B.E/MCA/M.Sc CS/IT or related).
What you'll do: build data pipelines end to end (ingest, transform, model, deliver), work with clients on their data, and use AI for query generation, data quality and debugging.
Must have: strong SQL (write, read, tune); Python for data; SQL Server and/or Postgres; at least one end-to-end data pipeline; data-analysis fundamentals; a GitHub with data projects.
Good to have: S3/Azure Blob, Airflow/mage.ai, DBT/Fabric, Snowflake/Databricks/BigQuery, GitLab CI/CD, Grafana, LLM/RAG awareness.
Compensation & terms: 6-month paid internship at ₹20,000/month, then ₹7 LPA CTC on conversion. Relocation to Hyderabad required.
Selection: Ziro assessment (Communication, Technical, AI interview, Coding), then the company's rounds (aptitude, AI screening, project build, in-office hackathon, technical panel, leadership).
Apply by Wed 21 Oct 2026.
Screening questions (please answer in your application):
1) Willing to relocate to Hyderabad and work onsite?
2) Do you accept a 6-month internship at ₹20k/month, then ₹7 LPA?
3) GitHub link + one project you built.
4) Graduation year, current city, notice period.

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Role Summary:
We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and Generative AI/Claude to work closely with clients, business stakeholders, and internal engineering teams. The ideal candidate will combine strong Data Engineering, Software Engineering, Databricks, and Generative AI skills with the ability to understand business problems and rapidly build, deploy, and optimize production-ready solutions. This is a client-facing, hands-on engineering role where you will work from problem discovery and solution design through POC development, production deployment, and ongoing optimization.
Key Responsibilities:
Forward Deployed Engineering
- Work directly with clients and stakeholders to understand business and technical requirements.
- Translate business problems into scalable data, AI, and software solutions.
- Design and develop POCs and rapidly validate technical solutions.
- Convert successful POCs into reliable, production-ready applications.
- Work closely with client engineering and data teams during implementation and deployment.
- Troubleshoot production issues and continuously optimize deployed solutions.
- Act as a technical bridge between clients, delivery teams, data engineers, AI engineers, and architects.
Databricks & Data Engineering
- Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
- Build and optimize data ingestion, transformation, and ETL/ELT pipelines.
- Work with Databricks Lakehouse, Delta Lake, and Unity Catalog.
- Develop Databricks Workflows and production data pipelines.
- Implement data processing solutions for structured and semi-structured datasets.
- Optimize Databricks workloads for performance, scalability, reliability, and cost.
- Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.
Generative AI & Claude
- Build enterprise AI solutions using Claude and other Large Language Models (LLMs).
- Integrate Claude APIs into applications and business workflows.
- Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data.
- Work with embeddings, vector search, semantic search, and knowledge retrieval.
- Develop AI-powered applications for summarization, classification, information extraction, question answering, and document processing.
- Implement prompt engineering, structured outputs, tool/function calling, and context management.
- Develop and integrate AI agents and multi-step AI workflows where applicable.
- Evaluate LLM responses for accuracy, relevance, groundedness, latency, and cost.
- Implement appropriate AI guardrails, security, and data privacy controls.
Production & Deployment
- Deploy AI and data solutions into production environments.
- Work with APIs, microservices, Git, CI/CD, containers, and cloud platforms.
- Monitor application and pipeline performance and troubleshoot issues.
- Collaborate with Data Scientists and ML Engineers to productionize AI/ML models.
- Ensure solutions meet security, scalability, reliability, and maintainability requirements.
Required Skills & Experience
- 4+ years of experience in Data Engineering, Software Engineering, AI/ML Engineering, or a related field.
- Strong hands-on experience with Databricks.
- Strong proficiency in Python, PySpark, and SQL.
- Experience with Delta Lake and Lakehouse Architecture.
- Experience working with Generative AI / LLMs.
- Hands-on experience with Claude / Anthropic APIs is preferred.
- Experience with RAG, embeddings, vector databases, and semantic search.
- Strong understanding of REST APIs and enterprise integrations.
- Experience developing production-grade applications and data pipelines.
- Strong problem-solving and troubleshooting capabilities.
- Excellent communication and client-facing skills.
Preferred Skills
- Experience with Claude Code / Anthropic ecosystem.
- Experience with OpenAI, Azure OpenAI, AWS Bedrock, or other LLM platforms.
- Experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
- Experience with Databricks Unity Catalog, Workflows, and MLflow.
- Experience with AWS, Azure, or GCP.
- Experience with Docker, Kubernetes, and CI/CD.
- Exposure to AI agents and agentic workflows.
- Knowledge of AI evaluation, guardrails, security, and responsible AI.
- Experience working in consulting, client delivery, or customer-facing engineering environments.
Key Competencies
- Strong customer-facing and stakeholder management skills.
- Ability to understand ambiguous business problems and translate them into technical solutions.
- Strong ownership and execution mindset.
- Ability to rapidly prototype, iterate, and productionize solutions.
- Strong analytical and troubleshooting skills.
- Comfortable working in fast-paced and dynamic client environments.
- Excellent written and verbal communication.
- Ability to work independently as well as collaboratively with distributed teams.
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Python pyspark, SQL, data engineer
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immediate to 15days.
About Solutionara
Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.
Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.
As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.
Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.
AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.
Role Overview
Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.
This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.
Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years
Key Responsibilities
Data Engineering
- Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
- Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
- Develop high-quality SQL and Python-based data processing solutions.
- Implement batch and incremental data-processing patterns.
- Develop reusable engineering components and frameworks.
- Support complex data migration and transformation activities.
- Perform source-to-target mapping and technical data analysis.
- Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.
Database & Platform Engineering
- Design and optimize relational database schemas and data structures.
- Analyze and improve SQL/query performance.
- Support indexing, partitioning, storage optimization, and database performance.
- Implement appropriate database security and access controls.
- Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
- Troubleshoot database and pipeline performance issues.
- Contribute to cloud data-platform configuration and optimization.
Data Quality
- Implement automated validation and data-quality controls.
- Develop reconciliation processes between source and target systems.
- Identify duplicate, incomplete, inconsistent, and invalid data.
- Implement cleansing, standardization, validation, and exception-management logic.
- Work with technical and business stakeholders to understand and implement business data rules.
Technical Delivery
- Convert technical designs into reliable production solutions.
- Participate in technical design and code reviews.
- Mentor junior/mid-level engineers.
- Support estimation and technical planning.
- Troubleshoot complex production and integration issues.
- Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
- Document technical designs, mappings, configurations, operational procedures, and engineering decisions.
Consulting & AI-Led Working
- Understand the business purpose behind assigned engineering requirements.
- Raise risks, assumptions, dependencies, and potential improvements proactively.
- Communicate effectively with client and internal stakeholders.
- Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
- Independently verify AI-generated code and recommendations before implementation.
- Identify opportunities for engineering automation and process improvement.
Required Qualifications
- 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
- Advanced SQL skills.
- Strong hands-on Python experience.
- Strong ETL/ELT development experience.
- Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
- Experience with data modeling and database design.
- Experience with AWS, Azure, or another major cloud platform.
- Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
- Experience with performance tuning and optimization.
- Experience with data validation and reconciliation.
- Strong troubleshooting and analytical skills.
- Ability to take ownership of engineering deliverables with limited supervision.
Preferred Qualifications
- Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
- Experience with manufacturing, retail, distribution, or consumer-goods data.
- Experience with CI/CD and infrastructure/platform engineering practices.
- Experience with API and event-driven integrations.
- Previous consulting or technology-services experience.
What Success Looks Like
- Pipelines and databases perform reliably at enterprise scale.
- Engineering solutions are maintainable, reusable, and well documented.
- Data issues are detected and addressed systematically.
- Junior engineers receive effective technical guidance.
- Problems are owned through resolution rather than simply escalated.
- Engineering decisions reflect both technical requirements and client business objectives.
About 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 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.
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
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.
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Hiring for Data Scientist / Senior Data Scientist
Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.
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.










