Opening For Data and AI Engineer

Tekskills; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Tekskills is seeking a senior data engineering professional to build end-to-end data pipelines for client analytics. You will collect, transform, and ensure data quality across diverse sources, collaborating with solution design and business teams to define requirements and assemble large datasets.

Responsibilities include designing analytics solutions, maintaining data model integrity with the client data architect, and enabling API access for data scientists.

Qualifications

• 7+ years in IT industry focusing on DWBI.
• Experience with Azure cloud platforms and data integration patterns.
• Strong knowledge of data modeling, data warehousing, and BI concepts.
• Hands-on with Data Lake, Databricks, Data Factory and BI projects.
• 4+ years SQL/PostgreSQL, BI solutions with 3rd party integration.
• Experience with Spark, Scala, Python, SQL scripting and NoSQL.
• Experience in large-scale data pipelines on cloud or on-premise.
• GenAI concepts like RAG, LangChain, LlamaIndex familiarity.

Responsibilities

• Build end-to-end data pipelines including data collection, transformation, quality and integration.
• Collaborate with design and business teams to define data requirements and assemble datasets.
• Design, implement and fine-tune analytics solutions to meet requirements.
• Ensure data model integrity with the data architect.
• Build infrastructure for ETL from diverse data sources.
• Create data tools for analytics and data science teams.
• Work with DevOps to support data and analytics solutions operations.
• Collaborate with data analysts and data scientists to design APIs.
• Provide weekly/status reporting to Client and Infosys managers.
• Be self-motivated, detail-oriented, and curious about AI trends.

Skills

Databricks

Azure Data Factory

SQL

Spark

Scala

Python

ADLS

GenAI concepts

Education

Bachelor or Masters degree in CS/IT

Job description

Description

Main Responsibilities

• Build end-to-end data pipelines including data collection, transformation, quality and integration solutions to facilitate Client data & analytics solutions.
• Collaborate with solution design and business requirements teams to identify data requirements and assemble large, complex data sets that meet the requirements
• Design, implement and fine-tune analytics solutions that meet business and technical requirements
• Work collaboratively with the Client data architect to ensure data model integrity
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Create data tools for analytics and data scientist teams that assist them in building and optimising the data models and solutions
• Work with the DevOps engineer to support the consistent operation of data & analytics solutions
• Work closely with the data analysts & data scientists to design and develop APIs
• Weekly and need basis Status reporting to Client and Infosys managers
• Self-motivated, able to work independently, and attention to details
• Curious about emerging AI trends and their implications for data engineering

7 - 12 years

Academic Qualification

• Bachelor or Masters degree in a related field (e.g. computer science, information technology, etc.)

Professional Experience

• Total experience of 7+ years in IT Industry in DWBI.
• Experience in Azure cloud platforms and technology
• Ability to define and develop data integration patterns and pipelines
• Strong knowledge of data modelling, data warehousing, and BI concepts
• Experience with Data Lake, Databricks, Data Factory, BI Dashboard, and BI implementation projects
• At least 4 years experience in SQL/PostgreSQL, data and BI solutions with integration to 3rd party tools
• Experience working with application server software (e.g. ERP), Spark, Scala, Python, SQL scripting languages, relational databases (e.g. SQL DB/DW), NoSQL platforms (e.g. HBase, MongoDB, Cassandra), cloud technologies (e.g. Azure)
• Highly experienced with processing large and complex datasets and building end-to-end data pipelines using on-premise or cloud-based data platforms
• Experienced in coding in data management, data warehousing or unstructured data environments
• Experience in the energy sector or other asset-intensive industries will be highly regarded
• Experience in using coding assistants (e.g. GitHub Copilot) for uplifting productivity in development
• Familiar with GenAI concepts like RAG, orchestration frameworks like LangChain and LlamaIndex, vector databases etc. to collaborate efficiently with data scientists and ML engineers in AI use cases

Mandatory skills

Databricks, Azure Data Factory, SQL, Spark, Scala, Python, ADLS, Familiar with GenAI concepts