Introduction: We at Entiovi Technologies provide digital transformation using new-age intelligent technologies for more than 9 years. We have clients located primarily in the US and Europe that are served by our Dedicated teams. This job is part of our expansion in India.

Location: Remote

About the role The

Data Engineer

in our AI & Data team will be responsible for designing and building the data structures and pipelines our AI Engineers rely on across

Azure ,

Snowflake ,

Databricks , and

Lakebase

(our managed Postgres / OLTP layer). The primary mission of this role is to enable the AI Engineering team translating the needs of machine-learning and computer-vision workflows into reliable, well-modelled, and cost-effective data foundations. Tasks include setting up new data pipelines and transformations, ingesting structured and unstructured data into the data lake and warehouse, monitoring the performance and cost-effectiveness of existing data jobs, and docking machine-learning processes into the existing data landscape. The Data Engineer works hand in hand with AI Engineers and is the go-to person for making trusted data available for models, products, and analytics.

Main Responsibilities As part of the AI & Data team, design and build the data structures, schemas, and models that AI Engineers depend on for training, feature engineering, and inference. Develop and orchestrate scalable data pipelines on

Databricks

(Spark, Delta Lake) and load curated, analytics-ready data into

Snowflake . Own data ingestion, transformation (ELT/ETL), and storage across the

Azure

cloud (e.g. ADLS, Data Factory, Event Hubs / Synapse), including structured, semi-structured, and unstructured data such as text, images, and video. Dock machine-learning and computer-vision models into the data pipelines and design the data flow that feeds and consumes those AI services. Sync curated lakehouse data into

Lakebase

(managed Postgres) for low-latency serving, manage change-data-capture back into Delta tables,



and support online feature stores and agent state for AI Engineers. Strong

API knowledge

and experience. Build and maintain API integrations and automated data ingestion from internal systems and external third-party sources. Monitor pipeline performance, reliability, and cost; troubleshoot failed jobs and optimize Snowflake and Databricks workloads. Implement data quality, validation, and lineage, and document the data dictionary and ETL processes. Partner with AI Engineers and stakeholders to translate model and business requirements into extensions of the data platform.

Skills, Qualifications & Education Bachelor’s degree in Computer Science, Data Engineering, or a related field. At least 4 years of work experience in data engineering or a similar data-focused role. Hands-on production experience with

Databricks

(Apache Spark, Delta Lake, notebooks, workflows). Hands-on production experience with

Snowflake

(data modelling, performance tuning, access control, cost management). Solid experience with

Microsoft Azure

data services (e.g. ADLS, Data Factory, Event Hubs / Synapse). Experience with

PostgreSQL

and OLTP databases; familiarity with

Lakebase

(Databricks-managed Postgres) is a strong plus. Working knowledge of

JavaScript / TypeScript , used for data APIs, microservices, or app-facing integrations. Strong expertise in

SQL

(will be tested during the recruitment process). Robust

Python

literacy, especially for data handling and pipeline development. Comfortable working with both structured and unstructured data; does not shy away from troubleshooting failed ETL processes or API integrations. Outstanding data-structure and data-modelling design skills. Working knowledge of machine-learning, NLP, or computer-vision workflows is a plus. Experience with dbt, Airflow, or Databricks Workflows, and with CI/CD and infrastructure-as-code, is a plus. Strong ability to translate ideas between technical and non-technical audiences. Curious, team-oriented, self-motivated, and organized; able to run multiple projects against tight deadlines.

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