Junior Data Engineer at Talent Pro · Pune · 1 - 2 years · ₹4L - ₹6L / yr · Bootstrapped · Posted 28 Nov 2025

Strong Data engineer profile
Mandatory (Experience 1): Must have 6 months+ of hands-on Data Engineering experience.
Mandatory (Experience 2): Must have end-to-end experience in building & maintaining ETL/ELT pipelines (not just BI/reporting).
Mandatory (Technical): Must have strong SQL capability
Preferred
Preferred (Experience): Worked on Call center data
Job Specific Criteria
CV Attachment is mandatory
Have you used Databricks or any notebook environment?
Have you worked on ETL/ELT workflow?
We have an alternate Saturdays working. Are you comfortable to WFH on 1st and 4th Saturday?

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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.
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.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Data Engineer
Experience - 5+ years
6-7 LPA
Remote
Duration: 1 month contract (We can take as a tentative, It can be extended)
Scope: Subscriber Activation, Churn, FTE and future reporting requirements, with BigQuery as the centralized data warehouse and Power BI as the proposed reporting layer.
Key Skills:
Strong hands-on experience with GCP & BigQuery
Data warehouse architecture, design and implementation
Data ingestion/integration across multiple source systems
ETL/ELT and data pipeline development
Data modelling for reporting and analytics
Experience integrating BigQuery with Power BI or similar reporting tools
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python, Hadoop, and Apache Spark.
- Develop efficient data processing and transformation workflows for large datasets.
- Write, optimize, and maintain complex SQL queries and PL/SQL procedures.
- Perform data extraction, transformation, and loading (ETL) from multiple data sources.
- Work with structured and unstructured data to support analytics and reporting requirements.
- Optimize data pipelines and queries for performance, scalability, and reliability.
- Ensure data quality, consistency, security, and integrity across data platforms.
- Collaborate with cross-functional teams to understand business requirements and deliver data engineering solutions.
- Use Git, automation, and CI/CD practices to support development and deployment.
Required Skills
- 4.5–10 years of experience in software development or data engineering.
- Strong proficiency in AWS
- Hands-on experience with Hadoop and Apache Spark.
- Good knowledge of SQL and PL/SQL, including query optimization and stored procedures.
- Experience in ETL development, data processing, and data pipeline design.
- Understanding of data warehousing concepts and distributed computing.
- Strong problem-solving, debugging, and performance-tuning skills.
8-12 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.
• Bachelor’s degree in computer science, Information Technology, or related field.
• Strong proficiency in PySpark, Python, SQL.
• Strong experience in data modeling, ETL/ELT pipeline development, and automation • Hands-on experience with performance tuning of data pipelines and workflow
• Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc.
• Experience with data modeling, ETL processes, Delta Lake and data warehousing.
• Experience on Delta Live Tables, Autoloader & Unity Catalog.
Preferred - Knowledge of the insurance industry and its data requirements.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Excellent communication and problem-solving skills to work effectively with diverse teams
• Excellent problem-solving skills and ability to work under tight deadlines.
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
We are looking for a skilled Data Engineer with 3+ years of hands-on experience in designing, developing, and maintaining end-to-end data engineering pipelines. The ideal candidate should have strong expertise in processing structured, semi-structured, and unstructured data, building scalable data pipelines, and implementing efficient data ingestion, transformation, storage, and processing solutions.
The candidate should be capable of handling the complete data engineering lifecycle, from data extraction and ingestion to transformation, integration, deployment, monitoring, and performance optimization.
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.












