Position : Data Engineer with Snowflake & AI Data Solutions Platform Projects Location : Remote (India)

Hi,

Synergy Technologies is a leader in technology services and consulting. We enable clients across the world to create and execute strategies .We help our clients find the right problems to solve, and to solve these effectively. We bring our expertise and innovation to every project we undertake

Position: Data Engineer with Snowflake & AI Data Solutions Platform Projects

Duration : Full Time

Location : / Remote (India)

3 to 5 Years

About the Role

Synergy Technologies is expanding its Data Engineering and Generative AI capabilities. We are looking for a hands-on Data

Engineer to work on Snowflake-based data solutions and emerging AI use cases using AWS services.

The candidate will work with backend engineers and technical leadership to develop data pipelines, transform enterprise

data, build proof-of-concepts (POCs), and prepare structured and unstructured data for AI applications. This role is suited

to an engineer with solid data engineering fundamentals who wants to grow into Snowflake and cloud-based AI

engineering.

Key Responsibilities

1. Data Engineering & Snowflake
2. • Develop and maintain data ingestion, transformation and processing pipelines.
3. • Write efficient SQL queries and implement data models for reporting and analytics.
4. • Work with Snowflake databases, schemas, tables, views and compute resources.
5. • Perform data cleansing, validation, reconciliation and data quality checks.
6. • Build POCs using existing client databases and enterprise datasets.
7. • Optimize query performance and resource utilization.
8. Python & Data Integration
9. • Develop Python scripts for data extraction, transformation and automation.
10. • Integrate data from relational databases, APIs, CSV files, JSON and other sources.
11. • Build reusable data processing components and scheduled workflows.
12. • Troubleshoot pipeline failures and maintain data consistency.
13. AWS & Generative AI Enablement
14. • Support data preparation and integration for AI applications built using AWS services.
15. • Learn and work with Amazon Bedrock and Amazon Nova for enterprise AI use cases.
16. • Prepare documents and datasets for knowledge assistants, retrieval-augmented generation (RAG) and AI-powered
17. • Develop data ingestion and retrieval workflows for structured and unstructured information.
18. • Assist in building evaluation datasets to measure AI response quality and reliability.
19. Collaboration & Delivery
20. • Collaborate with Go/backend developers to integrate data pipelines with application APIs.
21. • Work with technical leads and product stakeholders to translate business requirements into technical solutions.
22. • Participate in POC development, testing, documentation and client demonstrations.
23. • Follow coding standards, version control, secure data-handling practices and Agile delivery processes.
24. Required Skills
25. • 3–5 years of experience in Data Engineering, ETL development or a related role.
26. • Strong SQL skills, including joins, aggregations, CTEs, window functions and query optimization.
27. • Practical Python programming skills for data processing and automation.
28. • Experience building ETL/ELT pipelines and working with relational databases.
29. Synergy Technologies Data Engineering & AI
30. • Understanding of data modeling, data warehousing and data quality practices.
31. • Familiarity with Git, debugging and software development practices.
32. • Good analytical and problem-solving skills, with the ability to work independently on defined technical tasks.
33. Preferred Skills
34. • Hands-on exposure to Snowflake, including SQL development and data loading.
35. • Familiarity with AWS services such as S3, IAM, Lambda or Glue.
36. • Basic understanding of cloud data architectures.
37. • Exposure to dbt, Airflow or other data orchestration and transformation tools.
38. • Familiarity with REST APIs and JSON data.
39. • Interest in generative AI, large language models (LLMs), RAG and AI-assisted analytics.
40. Note: Prior hands-on Amazon Bedrock or Nova experience is an advantage, not a mandatory requirement. Strong data
41. engineering fundamentals and the ability to learn cloud AI services are more important.
42. What Success Looks Like
43. • Develop and validate a data pipeline for a selected POC.
44. • Contribute to a Snowflake-based analytics or data transformation use case.
45. • Prepare enterprise documents or datasets for an AI …