Data Analytics Engineer Hybrid

Job Title:

Data Analytics Engineer | INFT Solutions | Houston, Texas, USA (Hybrid)

Recruiting Company: INFT Solutions

Job Location:

North Houston, Texas, USA (Hybrid)

Job Type: Full-Time / Contract

• Urgent Hiring Requirement
• Hybrid Work Model
• Minimum 8+ Years of Experience Required
• Open to Candidates with Valid Work Authorization (Any Visa Category Considered)
• Immediate Availability Preferred

INFT Solutions is seeking an experienced Data Analytics Engineer to join a high-performing team in North Houston, Texas. This role is ideal for professionals with strong expertise in data engineering, analytics, reporting, and business intelligence who can transform complex data into actionable insights that drive business decision-making.

As a Data Analytics Engineer, you will be responsible for designing, building, and optimizing scalable data solutions that support analytics, reporting, and business intelligence initiatives. You will work closely with business stakeholders, data scientists, and engineering teams to develop robust data pipelines, ensure data quality, and deliver meaningful insights. The ideal candidate will possess extensive experience handling large-scale datasets, developing analytical frameworks, and implementing modern data architecture solutions.

This role requires strong technical expertise combined with excellent problem-solving skills and the ability to translate business requirements into data-driven solutions. You will play a critical role in helping the organization leverages data as a strategic business asset.

• Design, develop, and maintain scalable data pipelines and data integration solutions.
• Collect, cleanse, transform, and validate large datasets from multiple sources.
• Build and optimize data models, warehouses, and analytical data structures.
• Develop dashboards, reports, and business intelligence solutions.
• Perform advanced data analysis to identify trends, patterns, and business opportunities.
• Collaborate with business stakeholders to understand reporting and analytics requirements.
• Ensure data quality, consistency, governance, and compliance standards are maintained.
• Optimize database and query performance for large-scale analytics workloads.
• Support data migration, integration, and modernization projects.
• Create technical documentation, data dictionaries, and operational procedures.
• Troubleshoot data-related issues and implement sustainable solutions.
• Support enterprise analytics, forecasting, and decision-support initiatives.

• Bachelor’s Degree in Computer Science, Data Science, Information Technology, Engineering, Mathematics, Statistics, or a related field.
• Minimum 8 years of experience in Data Engineering, Data Analytics, Business Intelligence, or related roles.
• Strong experience working with large-scale enterprise data environments.
• Advanced SQL development and query optimization expertise.
• Experience with ETL/ELT processes and data integration frameworks.
• Strong knowledge of data warehousing concepts and dimensional modeling.
• Experience with data visualization and reporting tools such as Power BI, Tableau, or similar platforms.
• Proficiency in Python, SQL, or other analytics-focused programming languages.
• Experience with cloud-based data platforms and modern analytics architectures.
• Strong understanding of data governance, quality management, and security best practices.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong communication skills and stakeholder engagement experience.

• Experience with Azure, AWS, or Google Cloud data services.
• Knowledge of big data technologies such as Spark, Hadoop, or Databricks.
• Experience with Snowflake, Synapse Analytics, Redshift, or similar platforms.
• Familiarity with machine learning and predictive analytics concepts.
• Experience supporting enterprise digital transformation or analytics modernization initiatives.

For Data Analytics Engineer positions, clearly showcase projects where you transformed large datasets into measurable business outcomes. Highlight data pipeline development, analytics platforms used, dashboard implementations, query optimization achievements, cloud experience, and quantifiable results such as cost reductions, efficiency improvements, or revenue impact. This significantly improves your chances of being shortlisted.