Ascentt
Posted 142 days agoVerified live 2d ago
Data Engineer
Brief overview
Plano, TXIn-person
UndergradOr in progress
2+ yrsMinimum
35 H-1B approvalsDept. of Labor
2 green cardsCertified filings
ETL/ELT pipeline developmentPySparkDistributed computingDatabricksSnowflakeSQLPythonData WarehousingData ModelingCloud platforms (AWS, Azure, GCP)AirflowdbtAzure Data FactoryGitCI/CDDevOpsDelta Lake
About the company
Ascenttascentt.com
Ascentt is an AI, ML and Data Science solutions provider serving enterprise customers.
Visa sponsorship history
3 years sponsoring, last filed FY2026
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.35H-1B approved
95%approval rate
20new H-1B hires
2PERM certified
$148,741median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
202412
202511
202612
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20244
20255
20264
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
20252
Top sponsored roles
Manager-Data EngineeringSenior Software DeveloperPrincipal Data Scientist - IManager BIPrincipal ML Engineer - II
Job description
Summary
Ascentt is transforming the future of manufacturing through advanced Data Analytics, AI/ML, and Generative AI solutions. They are looking for a passionate Data Engineer to build scalable data platforms and optimize large-scale data pipelines while collaborating with Data Scientists, Analysts, and business stakeholders.
Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines for processing large volumes of structured and unstructured data
- Develop high-performance data processing solutions using PySpark and distributed computing frameworks
- Build, optimize, and manage data platforms on Databricks and/or Snowflake
- Write clean, efficient, and production-ready SQL queries and Python code for data transformation, automation, and analytics
- Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product teams, and Business stakeholders to deliver data-driven solutions
- Ensure data quality, governance, integrity, scalability, and reliability across enterprise data systems
- Monitor, troubleshoot, and optimize existing pipelines, workflows, and database performance
- Implement best practices around coding standards, testing, CI/CD, version control, and technical documentation
Skills
- 2–5 years of experience in Data Engineering or related roles
- Strong hands-on experience with Databricks and/or Snowflake
- Proficiency in SQL and Python programming
- Practical experience with PySpark and distributed data processing
- Solid understanding of Data Warehousing, ETL/ELT concepts, and Data Modeling
- Experience working with large-scale datasets in cloud-based environments
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field
- Experience with cloud platforms such as AWS, Azure, or GCP
- Familiarity with orchestration and transformation tools such as Airflow, dbt, or Azure Data Factory (ADF)
- Knowledge of Git, CI/CD pipelines, and DevOps best practices
- Exposure to Delta Lake, Lakehouse architecture, Kafka, Spark Streaming, or real-time data processing
- Experience working in Agile/Scrum environments is a plus
Qualifications
Must Haves
- 2–5 years of experience in Data Engineering or related roles
- Strong hands-on experience with Databricks and/or Snowflake
- Proficiency in SQL and Python programming
- Practical experience with PySpark and distributed data processing
- Solid understanding of Data Warehousing, ETL/ELT concepts, and Data Modeling
- Experience working with large-scale datasets in cloud-based environments
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field
Nice to Haves
- Experience with cloud platforms such as AWS, Azure, or GCP
- Familiarity with orchestration and transformation tools such as Airflow, dbt, or Azure Data Factory (ADF)
- Knowledge of Git, CI/CD pipelines, and DevOps best practices
- Exposure to Delta Lake, Lakehouse architecture, Kafka, Spark Streaming, or real-time data processing
- Experience working in Agile/Scrum environments is a plus
