Senior data engineer

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 Senior 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 by 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. Strong experience in Data Architecture. Strong knowledge of Git repositories. 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 Postgre SQL and OLTP databases; familiarity with Lakebase (Databricks-managed Postgres) is a strong plus. Working knowledge of Java Script / Type Script, 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, collaborative, self-motivated, and organized; able to run multiple projects against tight deadlines.

Location: Remote