4+ Graph Databases Jobs in India

Senior Data Engineer

• Data Engineering • Streaming Pipelines • Graph Databases • Entity Resolution

Role at a Glance Level

• Lead / Senior (Individual Contributor / Team Lead Track) Experience
• 7 - 10 years of relevant professional experience Location
• Remote (Pune Based Preferred) Employment Type
• Contract Industry Preference
• Any (Healthcare preferred - Payer / Provider experience strongly preferred)

About the Role

We are looking for a Senior Data Engineer with deep expertise in streaming architectures, graph database platforms, and large-scale data pipeline engineering. This is a high-ownership, hands-on role that sits at the intersection of real-time data infrastructure, entity resolution, and multi-database system design.

You will architect and build pipelines that drive a complex, multi-layered data platform - ingesting from diverse upstream sources, resolving entities at scale, and keeping graph, relational, search, and caching layers in sync. You will work closely with data architects, AI engineers, and product teams to deliver reliable, high-performance data infrastructure that powers downstream analytics and intelligent applications across any domain.

Key Responsibilities

Streaming & Ingestion Architecture

•Design and build production-grade CDC (Change Data Capture) pipelines using Apache Kafka, consuming events from PostgreSQL, SQL Server, and other RDBMS sources into a centralised knowledge graph.

•Architect multi-source ingestion connectors supporting schema evolution, backpressure handling, and at-least-once delivery guarantees across heterogeneous data sources.

•Configure and govern Confluent Schema Registry with Avro / Protobuf schemas across all Kafka topics; enforce backward and forward compatibility standards.

•Design micro-batch and streaming ETL/ELT workflows using Apache Spark or equivalent frameworks for bulk initial loads and ongoing incremental refresh patterns.

•Manage messaging workflows where required; define routing, dead-letter, and retry strategies appropriate to each integration pattern.

Graph Database Engineering

•Design, build, and optimise graph data models on a production graph database platform; Neo4j is preferred but experience with Amazon Neptune, ArangoDB, TigerGraph, or equivalent graph databases is valued.

•Author complex graph queries and traversal patterns - Cypher (Neo4j), Gremlin (Neptune/TinkerPop), or SPARQL - for both operational and analytical use cases.

•Own ingestion-side write strategies for the graph layer: batch import patterns, upsert logic, index management, and performance tuning under high write throughput.

•Collaborate with senior architects to ensure graph data models honour defined schema constraints and governance standards; apply constraint validation frameworks where applicable.

•Engineer reliable data flows across complementary stores - relational (PostgreSQL), search (Elasticsearch), caching (Redis), and time-series (TimescaleDB) - with consistent transaction semantics.

Entity Resolution & Data Quality

•Build probabilistic entity resolution engines for large-scale deduplication across master data domains - customers, products, entities, or records - leveraging record linkage concepts (Fellegi-Sunter model, blocking strategies, confidence thresholds) and libraries such as Splink, Zingg, or Dedupe.io.

•Define and enforce data quality validation rules at ingestion time; implement automated alerting for schema violations, volume anomalies, and SLA breaches.

•Design master data management patterns for cross-system entity matching and golden record creation; ensure consistency across all downstream consumers.

Data Platform & Lakehouse

•Design and implement data lakehouse patterns (Iceberg / Parquet on S3-compatible or Azure storage) for historical data retention, cost-efficient storage, and analytical workloads.

•Build and maintain ETL/ELT pipelines using Apache Spark or dbt; define transformation logic, partitioning strategies, and incremental processing patterns.

•Ensure data lineage, audit trail, and observability are built into pipeline design from the outset using OpenTelemetry or equivalent tooling.

Technical Leadership & Collaboration

•Contribute to a sub-team of data engineers; participate in sprint planning, design reviews, and on-call rotations for critical pipelines.

•Define and enforce coding standards, pipeline patterns, and infrastructure-as-code practices using Terraform, Docker, and Kubernetes.

•Drive proof-of-concept evaluations for new ingestion technologies, graph platforms, and data tooling relevant to the engagement.

Required Qualifications

Experience

•7 - 10 years of progressive experience in data engineering or a closely related discipline.

•Demonstrated track record of delivering production-grade streaming and CDC pipeline systems in enterprise environments across any industry vertical.

•Hands-on experience with graph database platforms in production - Neo4j preferred; Amazon Neptune, ArangoDB, TigerGraph, or equivalent is acceptable.

•Practical experience with entity resolution, fuzzy matching, or master data management at scale (500K+ records).

•Solid experience with multi-database architectures combining graph, relational, and search layers.

•Candidates from any industry are welcome; experience in regulated or data-intensive domains (financial services, retail, logistics, telecoms, healthcare) is advantageous.

Technical Skills

•Streaming & CDC: Apache Kafka

•Graph Databases: Production experience with at least one graph database platform - Neo4j (preferred), Amazon Neptune, ArangoDB, or TigerGraph; proficiency in the associated query language (Cypher, Gremlin, or SPARQL).

•Supporting Databases: PostgreSQL (relational), Elasticsearch (search), Redis (caching).

•Programming: Python (Advanced) - pipeline automation, data workflow scripting, testing; SQL at expert level for complex transformations and query optimisation.

•Entity Resolution: Probabilistic record linkage concepts; practical experience with Splink, Zingg, Dedupe.io, or a comparable library.

•Data Engineering: High-volume ETL/ELT pipeline design; Apache Spark for distributed processing; data lakehouse patterns (Iceberg, Parquet, Delta Lake).

•Cloud & Infrastructure: AWS or Azure - production delivery on at least one platform; Docker, Kubernetes, Terraform.

•Familiarity with semantic or schema standards - OWL 2, RDF, SHACL, JSON-LD - sufficient to write conformant graph data models against a defined schema.

•Experience with OpenTelemetry, distributed tracing, or observability tooling for pipeline monitoring and incident response.

•Prior work in compliance-driven data environments with audit trail, data masking, or access control requirements.

•Exposure to graph analytics and visualisation tooling such as Neo4j Bloom, Gephi, or equivalent.

•Experience with data governance platforms such as Microsoft Purview, Collibra, or Alation.

Preferred Qualifications

•Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related engineering discipline.

Join us to reimagine how businesses integrate data and automate processes – with AI at the core.

About FloData

FloData is re-imagining the iPaaS and Business Process Automation (BPA) space for a new era - one where business teams, not just IT, can integrate data, run automations, and solve ops bottlenecks using intuitive, AI-driven interfaces. We're a small, hands-on team with a deep technical foundation and strong industry connections. Backed by real-world learnings from our earlier platform version, we're now going all-in on building a generative AI-first experience.

The Opportunity

We’re looking for an GenAI Engineer to help build the intelligence layer of our new platform. From designing LLM-powered orchestration flows with LangGraph to building frameworks for evaluation and monitoring with LangSmith, you’ll shape how AI powers real-world enterprise workflows.

If you thrive on working at the frontier of LLM systems engineering, enjoy scaling prototypes into production-grade systems, and want to make AI reliable, explainable, and enterprise-ready - this is your chance to define a category-defining product.

What You'll Do

• Spend ~70% of your time architecting, prototyping, and productionizing AI systems (LLM orchestration, agents, evaluation, observability)
• Develop AI frameworks: orchestration (LangGraph), evaluation/monitoring (LangSmith), vector/graph DBs, and other GenAI infra
• Work with product engineers to seamlessly integrate AI services into frontend and backend workflows
• Build systems for AI evaluation, monitoring, and reliability to ensure trustworthy performance at scale
• Translate product needs into AI-first solutions, balancing rapid prototyping with enterprise-grade robustness
• Stay ahead of the curve by exploring emerging GenAI frameworks, tools, and research for practical application

Must Have

• 3–5 years of engineering experience, with at least 1-2 years in GenAI systems
• Hands-on experience with LangGraph, LangSmith, LangChain, or similar frameworks for orchestration/evaluation
• Deep understanding of LLM workflows: prompt engineering, fine-tuning, RAG, evaluation, monitoring, and observability
• A strong product mindset—comfortable bridging research-level concepts with production-ready business use cases
• Startup mindset: resourceful, pragmatic, and outcome-driven

Good To Have

• Experience integrating AI pipelines with enterprise applications and hybrid infra setups (AWS, on-prem, VPCs)
• Experience building AI-native user experiences (assistants, copilots, intelligent automation flows)
• Familiarity with enterprise SaaS/IT ecosystems (Salesforce, Oracle ERP, Netsuite, etc.)

Why Join Us

• Own the AI backbone of a generational product at the intersection of AI, automation, and enterprise data
• Work closely with founders and leadership with no layers of bureaucracy
• End-to-end ownership of AI systems you design and ship
• Be a thought partner in setting AI-first principles for both tech and culture
• Onsite in Hyderabad, with flexibility when needed

Sounds like you?

We'd love to talk. Apply now or reach out directly to explore this opportunity.

Role Overview

We are looking for a Tech Lead with a strong background in fintech, especially with experience or a strong interest in fraud prevention and Anti-Money Laundering (AML) technologies. 

This role is critical in leading our fintech product development, ensuring the integration of robust security measures, and guiding our team in Hyderabad towards delivering high-quality, secure, and compliant software solutions.

Responsibilities

• Lead the development of fintech solutions, focusing on fraud prevention and AML, using Typescript, ReactJs, Python, and SQL databases.
• Architect and deploy secure, scalable applications on AWS or Azure, adhering to the best practices in financial security and data protection.
• Design and manage databases with an emphasis on security, integrity, and performance, ensuring compliance with fintech regulatory standards.
• Guide and mentor the development team, promoting a culture of excellence, innovation, and continuous learning in the fintech space.
• Collaborate with stakeholders across the company, including product management, design, and QA, to ensure project alignment with business goals and regulatory requirements.
• Keep abreast of the latest trends and technologies in fintech, fraud prevention, and AML, applying this knowledge to drive the company's objectives.

Requirements

• 5-7 years of experience in software development, with a focus on fintech solutions and a strong understanding of fraud prevention and AML strategies.
• Expertise in Typescript, ReactJs, and familiarity with Python.
• Proven experience with SQL databases and cloud services (AWS or Azure), with certifications in these areas being a plus.
• Demonstrated ability to design and implement secure, high-performance software architectures in the fintech domain.
• Exceptional leadership and communication skills, with the ability to inspire and lead a team towards achieving excellence.
• A bachelor's degree in Computer Science, Engineering, or a related field, with additional certifications in fintech, security, or compliance being highly regarded.

Why Join Us?

• Opportunity to be at the cutting edge of fintech innovation, particularly in fraud prevention and AML.
• Contribute to a company with ambitious goals to revolutionize software development and make a historical impact.
• Be part of a visionary team dedicated to creating a lasting legacy in the tech industry.
• Work in an environment that values innovation, leadership, and the long-term success of its employees.

The candidate for the role will be responsible for enabling single view for the data from multiple sources. 

• Work on creating data pipelines to graph database from data lake
• Design graph database
• Write Graph Database queries for front end team to use for visualization
• Enable machine learning algorithms on graph databases
• Guide and enable junior team members

B.Tech with 2-7 years of experience

Must Have

Hands-on exposure to Graph Databases like Neo4J, Janus etc..

1. Hands-on exposure to programming and scripting language like Python and PySpark
2. Knowledge of working on cloud platforms like GCP, AWS etc.
3. Knowledge of Graph Query languages like CQL, Gremlin etc.
4. Knowledge and experience of Machine Learning 

Good to Have

• Knowledge of working on Hadoop environment

• Knowledge of graph algorithms

• Ability to work on tight deadlines