Sr. Data Engineer - Azure

• Job Title: Senior Data Engineer (Azure)
• Location: Ahmedabad, Gujarat
• Experience: 4+ years
• Job Type: Full Time
• Department: Data Engineering

About Simform

Simform is a premier digital engineering company specializing in Cloud, Data, AI/ML, and Experience Engineering to create seamless digital experiences and scalable products. Simform is a strong partner for Microsoft, Google Cloud, and Databricks. With a presence in 5+ countries, Simform primarily serves North America, the UK, and the Northern European market. Simform takes pride in being one of the most reputed employers in the region, having created a thriving work culture with a high work-life balance that gives a sense of freedom and opportunity to grow.

Role Overview

We are looking for a Senior Data Engineer (Azure) who is passionate about managing large-scale data, eager to take on challenges, and committed to delivering exceptional results. This role requires expertise in Azure data services, ETL pipelines, and database management. If you are a proactive problem solver with a strong technical background and a team player with a positive attitude, we want to hear from you.

Key Responsibilities

Design, develop, monitor, and maintain end-to-end data pipelines on Microsoft Fabric.

Work with Microsoft Fabric services such as

Fabric Pipelines (ETL/ELT)

Fabric Dataflows Gen2

• Fabric Lakehouse (Bronze/Silver/Gold architecture)
• Fabric Warehouse (SQL analytics engine)
• OneLake (unified storage)

Fabric Notebooks (PySpark / Spark SQL)

• Direct Lake mode for Power BI
• Fabric KQL Database / Eventstream / Real-Time Hub
• Fabric Shortcuts (cross‑workspace & multi-cloud virtualization)

Semantic Models

• Data Activator (alerting / action triggers)
• For ingestion, transformation, modeling, analytics, and real-time processing.
• Develop and optimize data ingestion, transformation, and analytical workflows for structured and unstructured data.
• Design efficient data models to ensure optimal performance in data processing and storage.
• Implement large-scale data ingestion pipelines capable of handling TBs of data.
• Build distributed batch or real-time data solutions using Apache Kafka, Apache Airflow, Databricks, or Fabric Real-Time Hub components.
• Build and maintain ETL/ELT pipelines for data integration and migration.
• Work extensively with relational databases (PostgreSQL, MySQL, SQL Server) and NoSQL databases (MongoDB, CosmosDB, Cassandra, GraphDB).
• Optimize SQL queries, performance tuning, indexing, partitioning, and denormalization strategies.
• Collaborate with cross-functional teams, including data scientists and software engineers, to integrate data solutions into production environments.
• Ensure data quality, integrity, governance, lineage, and compliance with security best practices.
• Participate in client interactions and stakeholder meetings to gather requirements and provide technical insights.

Required Skills & Qualifications

• Bachelor’s/Master’s degree in Computer Science, Data Engineering, or a related field.
• 4+ years of hands-on experience in data engineering, ETL development, and data pipeline implementation.
• Proficiency in Python and SQL for data processing and analysis.
• Strong expertise in Microsoft Fabric (Pipelines, Dataflows Gen2, Lakehouse, Warehouse, OneLake, Notebooks, Direct Lake, KQL Database, Real-Time Hub, Eventstream, Shortcuts, Semantic Models).
• Experience with big data frameworks like Spark, Kafka, and Airflow.
• Working knowledge of cloud data warehouse solutions such as Synapse, Snowflake, Redshift, or BigQuery.
• Experience with NoSQL databases (MongoDB, CosmosDB, Cassandra, GraphDB) and relational databases.
• Strong analytical and problem-solving skills.
• Ability to work independently, mentor peers, and meet tight deadlines.
• Excellent interpersonal and communication skills.
• Experience with cloud-based data architecture and security best practices.
• Fabric certifications are a plus (DP‑600, DP‑700, Fabric Analytics/Data Engineer Associate).

Preferred Qualifications (Nice to Have)

• Experience with data lake architectures.
• Knowledge of machine learning model deployment and data processing for AI applications.
• Prior experience in automated data pipeline deployment using CI/CD workflows.

Why Join Us

Young Team, Thriving Culture

Flat-hierarchical, friendly, engineering-oriented, and growth-focused culture.

Well-balanced learning and growth opportunities

• Free health insurance.
• Office facilities with a game zone, in-office kitchen with affordable lunch service, and free snacks.
• Sponsorship for certifications/events and library service.
• Flexible work timing, leaves for life events, WFH and hybrid options.