Senior Data Engineer

Job Summary:

We are seeking a Senior Data Engineer to design, build, and optimize scalable data platforms and pipelines that power analytics, reporting, and data-driven decision-making. This is a highly technical, hands-on role focused on data architecture, performance, reliability, and security across relational, NoSQL, and cloud-native storage systems. The ideal candidate brings deep experience in data engineering and software development and leads primarily through technical ownership and influence.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and architectures using SQL

Server, Azure Databricks, Azure Cosmos DB, and Azure Blob Storage.

• Build and optimize ETL/ELT workflows to ingest data from transactional systems,

APIs, and streaming sources into analytical data stores.

• Develop and maintain data models for both relational (SQL Server, Snowflake) and

NoSQL platforms (Cosmos DB), optimized for performance and analytical use cases.

• Implement data quality, validation, and monitoring frameworks to ensure accuracy,

reliability, and observability across pipelines.

• Optimize query performance, indexing strategies, partitioning, and storage costs

across SQL Server and cloud data platforms.

• Implement and enforce data security and compliance best practices, including role-

based access control, encryption, and secure data handling.

• Collaborate with analytics, application, and platform engineering teams to translate

business requirements into robust technical solutions.

• Build and maintain orchestration workflows using tools such as Azure Data Factory

and Apache Airflow.

• Support CI/CD pipelines for data solutions, including version control, automated

testing, and deployment.

• Evaluate and adopt new data technologies and patterns to continuously improve

platform scalability and resilience.

• Provide technical guidance and mentorship through code reviews, design

discussions, and best-practice advocacy.

Qualifications:

• Bachelor’s degree in computer science, Engineering, or a related field.

• 12+ years of experience in software development, with substantial hands-on

experience in data engineering.

• Strong expertise in SQL Server, including schema design, performance tuning,

indexing, and stored procedures.• Hands-on experience with Azure Cosmos DB (data modeling, partitioning,

throughput optimization).

• Experience working with Azure Blob Storage and cloud-based data lakes.

• Proficiency with Databricks, NoSQL databases (Cosmos DB, MongoDB, DynamoDB),

and distributed data processing.

• Deep understanding of ETL/ELT, data warehousing, and data modeling concepts.

• Experience with cloud platforms, primarily Azure (AWS exposure a plus).

• Hands-on experience with data pipeline orchestration tools such as Azure Data

Factory or Apache Airflow.

• Strong problem-solving skills and attention to detail, with a focus on scalability and

reliability.

• Ability to clearly communicate technical concepts to both technical and non-

technical stakeholders.

Preferred Qualifications:

• Experience preparing and serving data for machine learning and advanced analytics

use cases.

• Background in building and operating large-scale, distributed data environments.

• Experience working in Agile/Scrum teams.

• Familiarity with data governance, lineage, and observability tools in regulated

• environments.