About Mutually Human
At Mutually Human, we believe that innovation ensures relevancy. We help companies harness the power of Artificial Intelligence, Data, and Software through a holistic approach that emphasizes People, Process, and Technology. Our services are designed to solve key business challenges like optimizing operational efficiency, driving data-driven decision-making, and enhancing customer experiences. Join our team to help businesses stay ahead in an ever-evolving digital landscape.
Position Overview
The Data Engineer will design, implement, and optimize SQL-based data pipelines and databases, collaborating with cross-functional teams to develop scalable systems using Microsoft Fabric, Azure Data Lake, Databricks, and Snowflake for efficient data environments.
Key Responsibilities
Data Engineering & Optimization
- Design, build and maintain scalable, efficient ETL/ELT pipelines for data ingestion, transformation, and integration.
- Write, optimize, and manage SQL queries, stored procedures, and scripts to support analytics and reporting.
- Design and implement data models for business intelligence and analytical reporting.
- Ensure data quality, consistency, and reliability through best practices and validation techniques.
- Implement Medallion Architecture (Bronze, Silver, Gold layers) to enable scalable and structured data processing.
Work with Cutting-Edge Data & AI Tech
- Microsoft Fabric: Develop and manage dataflows, models, and SQL-driven analytics solutions.
- Databricks & Delta Lake: Optimize big data processing for large-scale transformations.
- Snowflake: Design modern data warehouses and data lakes that power AI-driven insights.
- Azure Data Lake: Implement high-scale storage solutions for AI and machine learning utilizing both structured and unstructured data.
Performance Optimization & DevOps
- Optimize SQL queries, indexing, and database performance tuning for efficiency and scalability.
- Work with CI/CD pipelines, automating deployments and testing for data workflows (using Git, Terraform, or Azure DevOps).
- Enable real-time monitoring and automation for enhanced pipeline reliability.
Path to Leadership & Senior Roles
- Take ownership of projects and begin leading technical initiatives.
- Mentor junior engineers and share knowledge within the team.
- Work towards designing data architecture and influencing strategic decisions.
- Collaborate with sales and business teams to translate needs into scalable data solutions.
AI/ML Enablement & Analytics
- Collaborate with data scientists and analysts to support AI/ML initiatives by integrating models into data pipelines.
- Enhance AI-driven data processing through automation and advanced transformations.
Collaboration & Governance
- Work closely with data analysts, business stakeholders, and product teams to gather requirements and deliver tailored data solutions.
Follow data governance best practices, ensuring compliance with security policies and regulatory standards.
Qualifications
Required Skills & Experience:
- SQL Proficiency: 3+ years of hands-on experience with advanced SQL for data analysis, modeling, and engineering.
- Data Pipeline Development: Experience with ETL/ELT tools and modern data engineering frameworks.
- Medallion Architecture Knowledge: Understanding of Bronze, Silver, and Gold data layers for structured data transformation.
- Cloud Data Engineering: Hands-on experience with Microsoft Fabric, Databricks, Azure Data Lake, or Snowflake.
- Database Management: Experience with SQL Server, PostgreSQL, SAP HANA, Progress, Oracle, Azure SQL or other relational databases.
- Programming Skills: Proficiency in Python, C# or Java for data transformations and automation.
- DevOps & Infrastructure: Experience with CI/CD pipelines, Git or Azure DevOps.
- Cloud Platforms: Working knowledge of Azure, AWS, or Google Cloud services.
Bonus Points for:
- Microsoft Data & AI certifications.
- Experience with BI tools like Power BI, Tableau, or Looker.
- Interest in ML model deployment and AI-driven analytics.
- Understanding of Azure and AWS networking concepts.
- Knowledge of data governance frameworks and compliance standards (GDPR, HIPAA, SOC 2).