Senior Data EngineerCanonical Data Modeling | Data Architecture | Entity Resolution | AI Data Platform

Location: Remote / Hybrid

Experience: 6–10 Years

Employment Type: Full time

About Us

We're building an enterprise AI platform that enables intelligent decision-making by unifying data across multiple enterprise systems.

Our platform integrates information from ERP, CRM, Accounting, Payroll, Scheduling, Project Management, Document Management, and other business applications to create a single trusted source of truth for AI-driven insights.

This is not a traditional ETL or pipeline engineering role.

We're looking for engineers who can design enterprise-grade data architectures, solve complex data integration challenges, and build scalable data platforms that power AI applications.

If your experience is limited to writing ETL jobs without owning data models, entity resolution, or data architecture, this role is unlikely to be the right fit.

What You'll Build

As a Senior Data Engineer, you'll own the data foundation that powers our enterprise AI platform.

You'll design canonical data models, resolve entity conflicts across multiple systems, build highly reliable ingestion frameworks, and create scalable serving layers optimized for AI workloads.

Your responsibilities will include

Designing canonical enterprise data models across multiple business systems

Building scalable data ingestion and synchronization pipelines

Implementing deterministic and probabilistic entity resolution

Designing survivorship and conflict-resolution strategies

Building Change Data Capture (CDC) and incremental synchronization frameworks

Developing replay-safe, idempotent data pipelines

Implementing data quality validation and anomaly detection

Designing data lineage, metadata management, and auditability

Optimizing analytical and transactional query performance

Building AI-ready data serving layers with conversational latency





Collaborating with AI Engineers and Backend Engineers to enable intelligent enterprise applications

Required Technical SkillsProgramming Languages

Python

Advanced SQL

Data Engineering

Canonical Data Modeling

Enterprise Data Architecture

Entity Resolution

Master Data Management (MDM)

Data Warehousing

Data Lake Architecture

Data Contracts

Data Governance

Data Processing

Change Data Capture (CDC)

Incremental Data Synchronization

Watermarking

Slowly Changing Dimensions (SCD)

Backfill Strategy

Replay Safety

Data Reconciliation

Schema Evolution

Data Modeling

Dimensional Modeling

Star Schema

Snowflake Schema

Normalization

Denormalization

Temporal Data Modeling

Business Semantic Modeling

Databases

PostgreSQL

SQL Optimization

Query Plan Analysis

Window Functions

Partitioning

Index Optimization

Materialized Views

Performance Tuning

Orchestration & Transformation

Hands-on experience with one or more:

Apache Airflow

Dagster

Prefect dbt

Data Quality & Observability

Great Expectations

Data Validation

Data Profiling

Data Lineage

Metadata Management

Freshness Monitoring

Completeness Monitoring

Volume Monitoring

Anomaly Detection

AI Data Infrastructure

Experience with one or more:

Vector Databases

Embedding Pipelines

Hybrid Search

Metadata Filtering

AI Retrieval Systems

RAG Data Pipelines

Streaming & Distributed Data

Apache Kafka

Event Streaming

Near Real-Time Data Processing

Batch Processing

Distributed Data Systems

Cloud & DevOps

Docker

Kubernetes

CI/CD

Infrastructure as Code

Object Storage

What We're Looking For





We're looking for engineers who:

Think beyond pipelines and focus on business semantics.

Have designed canonical data models across multiple enterprise systems.

Understand that data quality is a product feature, not a reporting metric.

Can solve complex entity resolution and reconciliation problems.

Build reliable, scalable, and AI-ready data platforms.

Take ownership of architecture, performance, governance, and operational excellence.

Nice to Have

Apache Spark

Delta Lake

Apache Iceberg

Apache Hudi

Snowflake

BigQuery

ClickHouse

Vector Search

OpenMetadata

DataHub

Unity Catalog

Multi-Tenant Data Platforms

Knowledge Graphs

Graph Databases

Why Join Us

You'll work on one of the most challenging problems in enterprise AI-building a unified data platform that enables AI systems to reason accurately across multiple business systems.

This is an opportunity to solve complex problems in data architecture, distributed systems, AI infrastructure, and enterprise-scale engineering while working alongside experienced Backend and AI Engineers.

Ideal Candidate

We're looking for engineers who have designed enterprise data architectures, owned canonical data models, resolved complex cross-system data challenges, and built scalable data platforms—not engineers whose experience is limited to writing ETL jobs or maintaining existing pipelines.

If you've built production-grade data platforms, understand business semantics, and enjoy solving complex data engineering problems, we'd love to hear from you.

Technologies We Work With

Languages: Python, SQL

Databases: PostgreSQL, Redis, Object Storage

Orchestration: Airflow, Dagster, Prefect, dbt

Streaming: Kafka, CDC

Cloud & DevOps: Docker, Kubernetes, CI/CD

AI Stack: Vector Databases, Embedding Pipelines, RAG, Metadata Management

Observability: Data Lineage, Monitoring, Validation, Audit Trails

📌 Senior Data Engineer (India)
🏢 Kramora Technologies
📍 India