Senior Data Engineer

Role Description

We are seeking an accomplished Senior Data Engineer to architect, design, develop, and maintain enterprise-grade data platforms, scalable data pipelines, and distributed data processing systems that support analytics, business intelligence, and machine learning initiatives across multiple business domains. In this role, you will be responsible for the end-to-end data engineering lifecycle, including:

• Translating business and analytical requirements into robust data architectures.
• Developing reliable ETL/ELT pipelines.
• Deploying cloud-native data solutions and supporting them throughout their operational lifespan.

The successful candidate will bring deep expertise in data engineering, distributed computing, cloud data platforms, and database technologies, combined with strong hands-on experience building scalable, secure, and high-performance data solutions. You will work closely with:

• Data scientists
• Business analysts
• Software engineers
• Solution architects
• DevOps engineers
• Stakeholders in an Agile environment

to deliver high-quality, reliable, and governed data platforms that directly support strategic business outcomes.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, Mathematics, or a closely related technical discipline.
• Five or more years of professional experience designing, developing, and supporting production-grade enterprise data engineering solutions, ETL pipelines, and cloud-based data platforms.
• Strong, demonstrable understanding of data structures, database design, distributed computing, data modeling, ETL/ELT methodologies, data warehousing concepts, and large-scale data architecture principles.
• Advanced working knowledge of Python, SQL, Spark, Scala, Java, and enterprise data engineering frameworks used to build scalable, high-performance data processing solutions.
• Hands-on, production-level experience designing and operating batch processing, streaming data pipelines, data lakes, and cloud-native data platforms using technologies such as Databricks, Snowflake, Apache Spark, Kafka, Airflow, or equivalent solutions.
• Proven experience working with relational and NoSQL databases including PostgreSQL, SQL Server, Oracle, MySQL, MongoDB, Cassandra, or equivalent database technologies.
• Strong SQL skills and meaningful experience designing dimensional models, star schemas, snowflake schemas, data marts, partitioning strategies, indexing, and enterprise-scale data warehouse solutions.
• Solid experience with Git-based version control, CI/CD pipelines, DevOps practices, release management, infrastructure automation, and Agile software development methodologies supporting enterprise data engineering initiatives.
• Hands-on experience deploying enterprise data platforms and analytics solutions on AWS, Azure, or Google Cloud Platform.
• Strong troubleshooting, analytical thinking, debugging, root-cause analysis, communication, and documentation skills.

Requirements

• Design, build, and continuously refine scalable batch and real-time data pipelines using Python, SQL, Spark, Scala, or equivalent technologies.
• Author secure, reusable, and production-quality ETL/ELT workflows adhering to enterprise coding standards, data governance policies, and security best practices.
• Develop scalable data integration solutions using modern cloud data platforms such as AWS, Azure, or Google Cloud.
• Design and implement robust data architectures, dimensional data models, data lakes, and data warehouses.
• Actively participate in enterprise data architecture discussions and technical design reviews.
• Continuously monitor, profile, and optimize ETL processes, Spark jobs, SQL queries, and database performance.
• Implement and maintain robust metadata management and data quality validation frameworks.
• Develop comprehensive automated testing frameworks for data pipelines and ETL workflows.
• Contribute to CI/CD pipeline design and infrastructure automation.
• Proactively identify data pipeline bottlenecks and operational risks.
• Collaborate effectively within Agile/Scrum delivery teams.
• Maintain clear, current, and comprehensive technical documentation.

Benefits

• Competitive base salary commensurate with experience.
• Comprehensive benefits package.