Walk-in Drive - Data Engineer (Virtual)

Simform

1d

About The Position

Simform is hiring a Senior Data Engineer specializing in Azure and Microsoft Fabric. The role focuses on managing large-scale data and designing, developing, monitoring, and maintaining end-to-end data solutions for ingestion, transformation, modeling, analytics, and real-time processing. The position works extensively with Microsoft Fabric services, data pipelines, relational and NoSQL databases, and cloud data architectures. The engineer collaborates with data scientists, software engineers, clients, and other stakeholders to integrate production data solutions and meet data quality, governance, lineage, security, and compliance needs.

Simform describes itself as a digital engineering company specializing in Cloud, Data, AI/ML, and Experience Engineering, with a presence in more than five countries and a primary client base in North America, the UK, and Northern Europe. It describes its culture as friendly, engineering-oriented, growth-focused, and supportive of work-life balance.

Requirements

• Bachelor’s or master’s degree in Computer Science, Data Engineering, or a related field.
• At least 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, including Pipelines, Dataflows Gen2, Lakehouse, Warehouse, OneLake, Notebooks, Direct Lake, KQL Database, Real-Time Hub, Eventstream, Shortcuts, and Semantic Models.
• Experience with big data frameworks such as Spark, Kafka, and Airflow.
• Working knowledge of cloud data warehouse solutions such as Synapse, Snowflake, Redshift, or BigQuery.
• Experience with NoSQL databases such as MongoDB, CosmosDB, Cassandra, or GraphDB, and with 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.

Nice To Haves

• Fabric certifications such as DP-600, DP-700, or Fabric Analytics/Data Engineer Associate.
• Experience with data lake architectures.
• Knowledge of machine learning model deployment and data processing for AI applications.
• Prior experience with automated data pipeline deployment using CI/CD workflows.

Responsibilities

• Design, develop, monitor, and maintain end-to-end data pipelines on Microsoft Fabric.
• Use Microsoft Fabric services for data ingestion, transformation, modeling, analytics, and real-time processing, including Pipelines, Dataflows Gen2, Lakehouse, Warehouse, OneLake, Notebooks, Direct Lake, KQL Database, Eventstream, Real-Time Hub, Shortcuts, Semantic Models, and Data Activator.
• Develop and optimize ingestion, transformation, and analytical workflows for structured and unstructured data.
• Design efficient data models for data-processing and storage performance.
• Implement large-scale data ingestion pipelines capable of handling terabytes 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 with relational and NoSQL databases and optimize SQL queries, performance, indexing, partitioning, and denormalization.
• Collaborate with 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.

Benefits

• Free health insurance.
• Office facilities with a game zone, an in-office kitchen with affordable lunch service, and free snacks.
• Sponsorship for certifications and events, and library service.
• Flexible work timing.
• Leaves for life events.
• Work-from-home and hybrid options.
• Learning and growth opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior