We are looking for a highly skilled and motivated Data Engineer to join our growing team in Dallas, TX. In this role, you will design and implement scalable data pipelines, build robust data infrastructure, and work closely with cross-functional teams to support advanced analytics and data-driven decision-making across the organization.
Key Responsibilities:- Build, optimize, and maintain scalable and reliable data pipelines (ETL/ELT)
- Develop data architectures and models to support analytics and reporting requirements
- Integrate and transform data from diverse sources such as APIs, flat files, logs, and databases
- Collaborate with Data Scientists, Analysts, and Software Engineers to understand data needs
- Ensure high data quality and integrity through validation and monitoring processes
- Automate workflows using orchestration tools like Apache Airflow or Prefect
- Monitor, troubleshoot, and optimize performance of data systems and pipelines
- Maintain and manage data infrastructure on cloud platforms (AWS/GCP/Azure)
- Implement data governance, security, and compliance best practices
- Create and maintain documentation of data architecture and pipelines
- Bachelor's or Master’s degree in Computer Science, Engineering, Information Systems, or a related field
- 3+ years of professional experience in Data Engineering or a similar role
- Strong hands-on experience with Python and SQL
- Experience with data processing frameworks like Apache Spark, Kafka, or Flink
- Proficiency with cloud data platforms (e.g., AWS Redshift, GCP BigQuery, Azure Synapse)
- Solid understanding of relational and NoSQL databases
- Experience with orchestration tools (Airflow, Luigi, Prefect)
- Familiarity with CI/CD processes and version control systems (e.g., Git)
- Strong analytical and problem-solving skills
- Excellent verbal and written communication skills
- Experience with real-time or streaming data systems
- Knowledge of data governance, privacy, and compliance standards (e.g., GDPR, HIPAA)
- Experience with Infrastructure-as-Code (IaC) tools like Terraform or CloudFormation
- Exposure to containerization and DevOps tools (Docker, Kubernetes)
- Familiarity with business intelligence tools like Tableau, Power BI, or Looker
About the role
- Describe the role and team the candidate will be joining
What you'll do
- Describe the specific responsibilities and job functions of the role
Qualifications
- Describe the experience and attributes of the ideal candidate
Skills Required
- 3+ years of professional experience in Data Engineering or a similar role
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field
- Strong hands-on experience with Python and SQL
- Experience with data processing frameworks like Apache Spark, Kafka, or Flink
- Proficiency with cloud data platforms (e.g., AWS Redshift, GCP BigQuery, Azure Synapse)
- Solid understanding of relational and NoSQL databases
- Experience with orchestration tools (Airflow, Luigi, Prefect)
What We Do
At Ascentt, we build AI that truly works for enterprises—secure, intelligent, and built to scale. With over 15 years of expertise in AI, data, and analytics, we empower businesses to transform complexity into clarity. Our AI solutions don’t just process data; they unlock insights, automate workflows, and accelerate decision-making—seamlessly fitting into enterprise systems while keeping security at the forefront. We believe AI should be practical, precise, and user-friendly—delivering real, measurable impact, not just hype. That’s why we focus on building AI that helps organizations move faster, work smarter, and concentrate on what truly matters. Discover the power of AI built for scale. Discover Ascentt.
