What are the responsibilities and job description for the Data Analyst / Data Engineer – Python, Automation & AI position at iVedha Inc.?
Role Overview
We are looking for a hands-on Data Analyst / Data Engineer with strong Python, SQL, data engineering, and automation skills, along with practical exposure to AI and Generative AI technologies.
The ideal candidate can work across the data lifecycle collecting, cleaning, transforming, analyzing, and integrating data while using scripting, automation, and AI to reduce manual effort and improve business processes.
This role is suitable for an intermediate to senior-level professional who enjoys solving practical data problems and building lightweight, scalable automation solutions.
Key Responsibilities
- Collect, clean, transform, validate, and analyze structured and unstructured data.
- Develop Python scripts to automate data processing, reporting, reconciliation, and operational tasks.
- Write and optimize SQL queries for data extraction, transformation, analysis, and reporting.
- Automate repetitive data workflows and manual business processes.
- Integrate data from APIs, databases, CSV/Excel files, SaaS platforms, and other enterprise systems.
- Perform data profiling, data quality checks, reconciliation, and exception handling.
- Build dashboards, reports, and analytical datasets for business and operational teams.
- Work with Python libraries such as Pandas, NumPy and related data-processing frameworks.
- Apply AI/Generative AI where appropriate for data extraction, classification, summarization, enrichment, analysis, and workflow automation.
- Work with LLMs and APIs such as OpenAI, Azure OpenAI or similar technologies.
- Support basic RAG, embeddings/vector search, document processing, and AI-assisted data workflows where required.
- Collaborate with data engineers, AI engineers, developers, business analysts, and business stakeholders.
- Document data pipelines, scripts, integrations, business rules, and automated workflows.
Required Skills
- 3 years of experience in data analysis, data engineering, software/data automation, or a related role.
- Strong hands-on experience with Python.
- Strong knowledge of SQL and relational databases.
- Experience with Pandas, NumPy, or similar Python data libraries.
- Experience building or supporting ETL/ELT pipelines.
- Ability to work with REST APIs, JSON, CSV, Excel and database integrations.
- Experience scripting and automating repetitive data or operational processes.
- Understanding of data quality, validation, transformation, reconciliation, and exception handling.
- Exposure to at least one cloud environment such as Azure, AWS or GCP.
- Practical understanding of Generative AI / LLM concepts and how AI can be incorporated into data workflows.
- Strong analytical and problem-solving skills.
Nice to Have
- Experience with Databricks, Snowflake, Microsoft Fabric, Azure Data Factory, Airflow or dbt.
- Experience with Power BI, Tableau or similar BI/reporting tools.
- Experience working with OpenAI, Azure OpenAI, Claude, Gemini or open-source LLMs.
- Understanding of RAG, embeddings, vector databases and AI agents.
- Experience with workflow automation tools or building Python-based automation.
- Familiarity with Git, CI/CD and basic DevOps practices.
- Experience working with large datasets or enterprise data platforms.
Pay: From $75,000.00 per year
Work Location: In person
Salary : $75,000