Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : PySpark
Good to have skills : NA
Minimum
3 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Custom Software Engineer, a typical day involves designing, building, and configuring applications tailored to fulfill specific business processes and application needs. you will lead the technical design, development, and deployment of data engineering, machine learning, and knowledge graph solutions. You will manage tech teams, work closely with stakeholders, and build intelligent data platforms and AI-driven applications.
Roles & Responsibilities:
Technical Leadership: Act as a Subject Matter Expert (SME) in Data, ML, and Knowledge Graphs. Lead technical teams, make key architectural decisions, and guide project direction.
Data Pipelines: Design and build large-scale data pipelines, enterprise data lakes/lakehouses, and real-time streaming platforms.
Knowledge Graphs & AI: Build Knowledge Graph solutions, ontologies, and semantic models. Integrate Knowledge Graphs with Large Language Models (LLMs) and GraphRAG applications.
ML Deployment: Develop and deploy machine learning models into production using MLOps best practices.
Governance & Operations: Set standards for data governance, metadata management, code quality, and smooth CI/CD (DataOps/MLOps) workflows.
Mentorship: Guide, mentor, and upskill team members while managing technical project risks.
Professional & Technical Skills:
Strong expertise in PySpark, Apache Spark, and Databricks.
Machine Learning experience using Python, TensorFlow, PyTorch, or Scikit-learn.
Hands-on experience with Knowledge Graphs and Graph Databases (e.g., AWS Neptune, Neo4j, Stardog) using RDF, OWL, and SPARQL.
Experience with Generative AI, LLMs, and GraphRAG integration.
Proficiency in SQL, NoSQL databases, and building batch/streaming pipelines.
Cloud experience with at least one platform: Azure, AWS, or GCP.
Good to Have:
Microsoft Fabric, Azure Synapse, or Azure ML.
Vector databases, LangChain, or Semantic Kernel.
MLflow or Kubeflow.
Additional Information:
- The candidate should have PySpark / Data Engineering: 3+ years.
- Machine Learning / AI: 3+ years.
Knowledge Graphs: 2+ years.
Education: 15 years of full-time education.
Job Location: Bengaluru, India.
Recommended Certifications(Good to Have)
Data: Azure Data Engineer (DP-203), Microsoft Fabric (DP-600), or Databricks Data Engineer Professional.
AI/ML: Azure AI Engineer (AI-102) or Databricks ML Professional.
Graph: Neo4j Certified Professional.
Architecture: TOGAF or Azure Solutions Architect (AZ-305).
