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Senior Data Engineer
Entiovi Technologies
Entiovi is a technology solution & services provider helping its customers to grow their b
Job Description
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.
● 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 6 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 modeling, 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-modeling 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.
Category
Data Analysts (Information Design and Documentaion) Software Engineer (Software and Web Development) Data Engineer (Software and Web Development)
Expertise
- Python - 1 Year - Intermediate SQL - 4 Years - Intermediate PostgreSQL - 3 Years - Intermediate JavaScript - 1 Year - Intermediate AWS - 4 Years - Intermediate Azure - 4 Years - Intermediate Natural Language Processing - 1 Year - Intermediate Machine Learning - 1 Year - Intermediate Typescript - 1 Year - Intermediate CI/CD - 2 Years - Intermediate ETL(Extract, Transform, Load) - 5 Years - Intermediate Snowflake - 4 Years - Intermediate Computer Vision - 1 Year - Intermediate Databricks - 5 Years - Intermediate
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