We are seeking a results-driven engineer to design, develop, and maintain end-to-end web solutions that support AI and automation initiatives. This role requires expertise in modern front-end and back-end technologies, API integration, and cloud-based infrastructure.

Responsibilities

• Design and implement enterprise-wide data architecture frameworks that support cross-division data integration and usability.

• Develop scalable data pipelines and workflows (ETL/ELT) to support analytics, reporting, and machine learning workloads.

• Collaborate with stakeholders across business units to identify data requirements and consolidate sources.

• Lead efforts in data modeling, documentation, and establishing common data definitions and practices.

• Define and implement data governance, data quality, and security frameworks aligned with compliance requirements.

• Evaluate and recommend modern data technologies to support ongoing evolution of data infrastructure.

• Partner with data engineers, analysts, and scientists to ensure data availability and usability.

• Contribute to team growth by mentoring junior team members and promoting best practices in data engineering and architecture

Must-Have Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or a related field.

• Proven experience as a Data Architect, Senior Data Engineer, or in a similar data-focused role.

• Strong knowledge of database management systems, both SQL (e.g., Azure SQL, PostgreSQL) and NoSQL (e.g., Cosmos DB, MongoDB).

• Proficiency in data modeling, data warehousing, and ETL/ELT pipelines using tools such as Apache Airflow, or Azure Data Factory.

• Experience with big data technologies such as Apache Spark, Databricks, or similar.

• Familiarity with cloud data platforms, preferably Microsoft Azure

• Strong understanding of data governance, data quality, and data security practices.

• Familiarity with containerization and orchestration tools like Docker and Kubernetes.

• Understanding of CI/CD pipelines and DevOps practices for data workflows.

• Knowledge of data privacy regulations such as GDPR, CCPA, or similar compliance frameworks.

Nice-to-Have Qualifications

• Experience with AI and machine learning frameworks (e.g., TensorFlow, PyTorch, Azure ML).

• Knowledge of data visualization tools (e.g., Power BI, Tableau, Looker) and how to support reporting layers.

• Exposure to real-time data processing and streaming technologies (e.g., Kafka, Azure Event Hubs, Stream Analytics).

• Hands-on experience with Python, PySpark, or similar scripting languages for data transformation.

Please refer to job description.