Job Description

Location: Dallas, TX

Job description:

We are seeking a highly motivated and skilled Data Engineer to help us build and maintain efficient data architectures, pipelines, and reporting solutions. The ideal candidate will have a strong foundation in database management, ETL processes, and BI tools like Power BI and Tableau. You will work closely with both technical and business stakeholders to ensure our data is accessible, clean, and ready for analysis.

Responsibilities:

• Design & Build Data Pipelines: Design and implement scalable and reliable ETL (Extract, Transform, Load) processes to gather data from multiple sources and integrate them into centralized data warehouses or lakes.
• Database Management: Manage relational and non-relational databases, ensuring data integrity, security, and accessibility. Optimize SQL queries for performance and efficient data retrieval.
• Business Intelligence & Reporting: Develop and maintain interactive dashboards and reports using Power BI and Tableau.
• Data Transformation & Modeling: Cleanse, transform, and structure raw data into formats suitable for analysis. Develop efficient data models that enhance the performance of BI tools.
• Monitor & Optimize Data Pipelines: Continuously monitor the performance and reliability of data pipelines, troubleshoot issues, and implement improvements for better scalability.
• Collaborate with Teams: Work closely with data scientists, analysts, and business teams to understand reporting needs and provide insights into business performance.
• Ensure data-driven decisions are based on accurate and well-structured data.
• Ensure the dashboards are intuitive, user-friendly, and deliver actionable insights to business stakeholders.
• Data Governance: Adhere to best practices for data governance, ensuring compliance with security protocols and data privacy standards.

Requirements:

• Power BI & Tableau: Hands-on experience building dashboards and reports using Power BI and Tableau.
• Proficiency in creating advanced visualizations, reports, and KPIs.
• Database Expertise: Strong knowledge of SQL and experience working with relational databases (e.g., SQL Server, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• ETL Tools & Data Integration: Familiarity with ETL tools (Azure Data Factory, Talend, Apache NiFi) for data extraction, transformation, and loading.
• Experience building data pipelines from scratch.
• Data Warehousing Solutions: Knowledge of data warehousing concepts and platforms (e.g., Snowflake, Amazon Redshift, Google BigQuery).
• Cloud Technologies: Experience with cloud platforms like AWS, Azure, or Google Cloud for data storage, processing, and analysis.
• Programming Languages: Experience in Python or R for data wrangling, transformation, and analysis.
• Version Control: Experience with version control tools like Git to manage and track changes in scripts and code.
• Strong problem-solving and analytical skills, with attention to detail.
• Excellent communication skills, both written and verbal.