Data Engineer

Ascendo Resources; Lewisville (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

Ascendo Resources seeks a Principal Data Engineer to lead enterprise data platform design, scalable pipelines, and governance to enable advanced analytics. You will partner with engineering and business teams to translate complex data needs into trusted, actionable insights.

The role emphasizes hands-on leadership, cloud proficiency, and mentorship, across data modeling, architecture, and data quality initiatives, in a fast-paced enterprise environment.

Qualifications

• 12+ years of experience in data engineering, analytics, or related roles.
• Experience designing enterprise data solutions and platforms.
• Strong knowledge of cloud-based data platforms and modern practices.
• Advanced SQL, ETL/ELT, and distributed processing experience.
• Experience with Databricks, cloud data warehouses, or lakehouse architectures.
• Ability to translate requirements into scalable data solutions.

Responsibilities

• Lead design and implementation of enterprise-scale data platforms.
• Develop scalable data pipelines and analytics-ready datasets.
• Design data models and architectures to support BI and reporting.
• Build data processing solutions using modern cloud technologies.
• Establish data quality, validation, and monitoring frameworks.
• Create architecture diagrams, mappings, lineage, and data definitions.
• Implement governance including access controls and metadata management.
• Collaborate with engineers, analysts, and stakeholders to deliver reliable data solutions.
• Provide technical leadership and mentorship to teams.

Skills

SQL

Databricks

ETL/ELT

Data modeling

Data governance

Cloud data platforms

CI/CD

Terraform

dbt

Tools

Databricks

Cloud data warehouses

Lakehouse architectures

Job description

We are seeking a highly experienced Principal Data Engineer to lead the design, development, and optimization of enterprise data solutions. This role will focus on building scalable data platforms, developing reliable data pipelines, enabling advanced analytics, and establishing strong data governance practices.

The ideal candidate is a hands-on technical leader with deep experience in cloud data engineering, enterprise architecture, analytics enablement, and secure data management. This individual will work closely with technical teams and business stakeholders to transform complex data environments into trusted, actionable insights.

Responsibilities

• Lead the design and implementation of enterprise-scale data platforms and solutions.
• Develop scalable data pipelines, curated datasets, and analytics-ready data products.
• Design data architectures, integration strategies, and data models that support business intelligence and reporting needs.
• Build and optimize data processing solutions using modern cloud data technologies.
• Establish and maintain data quality standards, validation processes, and monitoring frameworks.
• Create technical documentation including architecture diagrams, data mappings, lineage documentation, and data definitions.
• Implement governance practices including access controls, security standards, metadata management, and protection of sensitive information.
• Partner with engineering teams, analysts, business stakeholders, and external partners to deliver reliable data solutions.
• Provide technical leadership, mentorship, and guidance to engineering teams.
• Support analytics, automation, and advanced data initiatives across the organization.

Required Qualifications

• 12+ years of experience in data engineering, data architecture, analytics engineering, or related technical roles.
• Extensive experience designing and building enterprise data solutions.
• Strong knowledge of cloud-based data platforms and modern data engineering practices.
• Advanced experience with SQL, data pipelines, ETL/ELT processes, and distributed data processing.
• Experience with platforms such as Databricks, cloud data warehouses, lakehouse architectures, or similar technologies.
• Experience designing enterprise data models, semantic layers, and reporting datasets.
• Strong understanding of data governance, security, compliance, and privacy practices.
• Ability to collaborate with technical teams and business leaders to translate requirements into scalable solutions.

Preferred Qualifications

• Experience with enterprise analytics platforms and business intelligence solutions.
• Experience working with sensitive business data, reporting environments, or regulated data domains.
• Experience with DevOps practices including Git, CI/CD pipelines, infrastructure automation, Terraform, or similar tools.
• Experience with data transformation frameworks such as dbt.
• Experience supporting artificial intelligence, machine learning, or predictive analytics initiatives.
• Cloud certifications or professional data engineering certifications.