Opening position For Data Engineer

Role & responsibilities

• 4 to 9 years of hands-on experience in Data Engineering and building scalable data solutions.
• Strong hands-on experience with cloud-based data engineering platforms. AWS experience is preferred, but candidates with Azure experience are also welcome.

Technical Skills

• Strong hands-on expertise in Python and PySpark for large-scale data processing.
• Advanced proficiency in SQL, including complex queries, query optimization, and data analysis.
• Experience with AWS data engineering services is preferred. Relevant Azure data engineering experience is also acceptable.
• Strong understanding of Apache Spark and distributed data processing systems.
• Experience designing, developing, and maintaining scalable, high-performance ETL/ELT data pipelines.
• Experience in data ingestion, transformation, integration, and processing from multiple data sources.
• Experience working with structured, semi-structured, and unstructured data, including JSON, logs, PDFs, and other file formats.
• Strong knowledge of relational and non-relational databases.
• Experience in data quality checks, validation, performance tuning, and optimization.

Secondary Skills Generative AI (GenAI)

• Exposure to Generative AI (GenAI) and LLM-based applications.
• Understanding of RAG (Retrieval-Augmented Generation) and vector databases.
• Experience integrating LLMs with data pipelines and cloud-based data platforms.
• Familiarity with frameworks such as LangChain or LlamaIndex.
• Understanding of data preparation, ingestion, and transformation for GenAI applications.
• Exposure to embedding generation, document processing, and vector search.
• Familiarity with AI/ML workflows and GenAI use cases in data engineering.

GenAI experience is an added advantage and is not mandatory.

Analytical & Problem-Solving Skills

• Ability to perform in-depth data analysis and troubleshoot complex data-related issues.
• Proven experience building scalable data solutions to address complex business requirements.
• Strong problem-solving and analytical skills.

Soft Skills

• Strong verbal and written communication skills.
• Good organizational and stakeholder-management skills.
• Proactive self-starter with the ability to work independently and take ownership.

Technical Agility

• Ability to adapt quickly to new technologies and data platforms.
• Willingness to stay updated with emerging trends and best practices in Data Engineering, cloud platforms, Big Data technologies, and Generative AI.