Data Engineer

Job Description: Data Engineer (Data, Power BI & Secure Architecture)Role OverviewWe are seeking a highly skilled Data Engineer to design, build, and optimize our enterprise data infrastructure. In this role, you will bridge the gap between raw data engineering and business-facing analytics. You will be responsible for building scalable ETL/ELT pipelines, implementing a secure Lakehouse/Data Warehouse architecture, and creating high-performance semantic models within Power BI.A critical component of this role involves data security, specifically managing SSL/TLS protocols to ensure all data-in-transit across databases, cloud networks, and visualization tools is fully encrypted and compliant with global security standards.Key Responsibilities

• Data Pipeline & Architecture Engineering: Design, build, and maintain robust, automated data pipelines (ETL/ELT) utilizing Python, SQL, and cloud native orchestration tools (e.g., Apache Airflow, Azure Data Factory).
• Data Visualization & BI Development: Architect and optimize enterprise-level Power BI dashboards, reports, and data flows. Design complex, performant semantic models using DAX and Power Query (M). [1]
• Security & Infrastructure Hardening: Implement and enforce end-to-end security measures. You will configure and manage SSL/TLS certificates across database connections, API endpoints, and gateway clusters to guarantee encrypted data transport.
• Data Modeling & Warehousing: Develop scalable database schemas using Medallion Architecture (Bronze/Silver/Gold), Star/Snowflake schemas, and views tailored for business intelligence efficiency. [1]
• Performance Tuning: Optimize deep SQL queries (window functions, CTEs) and database indexing. Tune Power BI report refresh rates, DirectQuery performance, and storage engine constraints. [1]
• Cross-functional Collaboration: Partner closely with data scientists, analysts, and security compliance teams to deliver reliable, trusted data assets.

Required Technical Skills1. Core Data Engineering

• Languages: Advanced SQL (fluent in query tuning, indexing, and complex joins) and Python/PySpark.
• Platforms & Lakes: Solid experience with cloud data platforms like Snowflake, Databricks, Azure Synapse, or AWS Redshift.
• Orchestration: Experience with tools like Airflow, dbt, or cloud-native pipelines. [1, 2, 3, 4]

2. Power BI Expertise

• Deep knowledge of Power BI Desktop, Power BI Service, and deployment pipelines.
• Expert proficiency in writing optimized DAX calculations and M code.
• Experience configuring and maintaining On-Premises Data Gateways and managing row-level security (RLS/Object-level security). [1]

3. Security & Connectivity (SSL/TLS)

• Strong hands-on experience enforcing SSL/TLS encryption for database connections (e.g., PostgreSQL, SQL Server, Oracle).
• Experience with certificate management (issuing, renewing, and binding SSL certificates) for data servers, secure webhooks, and REST APIs.
• Familiarity with network security protocols, Virtual Private Networks (VPNs), firewalls, and cloud security frameworks (e.g., Azure Key Vault, AWS Secrets Manager).

Qualifications & Experience

• Education: Bachelors or Master’s degree in Computer Science, Information Technology, Software Engineering, or a related quantitative field. [1]
• Experience: 3–5+ years of dedicated experience working in data engineering or data architecture capacities. [1]
• Certifications (Preferred but not required):
• PL-300: Microsoft Power BI Data Analyst
• DP-203: Microsoft Azure Data Engineer Associate
• CompTIA Security+ or equivalent knowledge in network security/encryption.