Quality Data Engineer

Information Technology Senior Management Forum

Spring (TX)

On-site

USD 105,000 - 162,000

Full time

3 days ago

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Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Long term and short term disability

Employee assistance program

Flexible spending account

Life insurance

Parental leave (4-12 weeks, tenure)

11 paid holidays

Additional flexible paid vacation and/

Job summary

Information Technology Senior Management Forum is seeking a senior data engineering leader to shape enterprise data platforms and pipelines for analytics and AI/ML outcomes. You will mentor staff, set governance standards, and drive data mesh, medallion, and GenAI-ready architectures to enable scalable, secure data delivery.

The role emphasizes collaboration with cross-functional partners and delivering high-quality data pipelines for batch, streaming, and real-time workloads.

Qualifications

A four-year or graduate degree in a relevant field.
7–10 years of work experience in analytics, data science, or related field.
Strong experience with cloud platforms: AWS, Azure.
Strong experience with Data Lakes, Lakehouse, Data Warehousing.
Strong experience with ETL/ELT and pipeline orchestration.
Python and SQL proficiency (mandatory).
Scala/Java a plus.
Experience with streaming and real-time data systems.
Experience with data modeling and governance.
Experience with MLOps and model deployment pipelines.
Experience with modern architectures: Data Mesh, Medallion, API-driven data services.

Responsibilities

Lead the data engineering team supporting projects and coordinate with partners to align deliverables.
Develop solutions for complex deals and contribute to enterprise solution design.
Oversee design, development, and maintenance of databases.
Resolve critical incidents, produce data models, and lead model conversion.
Provide expert guidance and mentor junior staff to boost team effectiveness.
Create an enterprise-wide blueprint for data storage, integration, access, and governance.
Manage platforms enabling downstream insights and solutions.
Design data warehouses and data lakes meeting quality requirements.

Skills

Agile Methodology

Effective Communication

Digital Fluency

Data Analysis

Data Architecture

Education

Four-year or Graduate Degree

Tools

AWS

Azure

Apache Spark

ETL/ELT

Data Mesh

Medallion

API-driven data services

NoSQL

Python

SQL

Java

MLOps

Job description

Shape enterprise data platforms and pipelines to power analytics and AI/ML outcomes while driving data quality, security, and governance.

Responsibilities

Lead the data engineering team supporting application projects and coordinate with cross-functional partners to align data engineering deliverables with project outcomes
Develop solutions for complex deals and contribute to solution design for enterprise requirements
Oversee design, development, and maintenance of intricate databases
Resolve critical database incidents, produce data models, and lead model conversion efforts
Provide expert guidance, exercise independent judgment, and mentor lower-level employees to support team effectiveness
Create an enterprise-wide blueprint for how data is stored, integrated, accessed, and governed
Manage technical platforms that enable downstream insights and solutions
Design PS quality data warehouses and data lakes
Define architectural patterns such as medallion architecture, data mesh, and data fabric
Establish data standards and automated interoperability rules
Design data warehouses and data lakes that meet quality business requirements
Define and implement enterprise-grade data architectures for batch, streaming, and real-time workloads for large-scale structured and unstructured data
Build scalable, secure, high-performance data platforms for BI, advanced analytics, and AI/ML use cases
Set data modeling standards and reusable frameworks across the organization
Lead enterprise data strategy, aligning data initiatives with business goals, AI goals, and digital transformation priorities
Identify and prioritize high-value analytics and AI opportunities using telemetry, operational, and product data
Drive data monetization, standardization, and governance frameworks
Define a roadmap for modern data stack adoption, including cloud-native, lakehouse, streaming, and GenAI-ready architectures
Partner with Data Scientists to productionize ML/AI models into scalable systems
Build and optimize data pipelines, feature engineering frameworks, and MLOps workflows
Lead design, development, and deployment of complex data pipelines and distributed systems
Drive adoption of new technologies including GenAI, agentic systems, streaming architectures, and data mesh
Ensure solutions meet performance, reliability, and cost optimization goals
Ensure compliance with data governance, privacy, security, and compliance standards in alignment with HP cybersecurity and privacy guidelines
Maintain master data management, access controls, audits, metadata management, and data hierarchy
Establish data quality frameworks, lineage, observability, and monitoring mechanisms
Implement best practices across the data lifecycle
Influence executive leadership, architecture boards, and cross-functional stakeholders on data strategy decisions
Represent the organization in industry forums, publications, and innovation initiatives
Translate business goals into platform capabilities
Support outcomes including faster automated analytics, enhanced AI/ML readiness, self-service tools, and operational reporting
Enable data-driven decision making

Requirements

Four-year or Graduate Degree in Computer Science, Information Systems, Engineering, Statistics/Mathematics, Machine Learning, Data Analytics, and demonstrated competence
7-10 years of work experience, preferably in analytics, data science, reporting, or a related field
Strong experience with cloud platforms: AWS, Azure (data services, analytics, storage)
Strong experience with data platforms: Data Lakes, Lakehouse, Data Warehousing
Strong experience with ETL/ELT and pipeline orchestration
Python and SQL (mandatory)
Scala/Java (good to have)
Experience with streaming and real-time data systems
Experience with data modeling and governance
Experience with MLOps and model deployment pipelines
Experience with modern architecture: Data Mesh, Medallion, API-driven data services

Technologies

AWS, Azure
Data Lakes, Lakehouse, Data Warehousing
ETL/ELT
Python, SQL
Scala, Java
Streaming and real-time data systems
Data Mesh, Medallion
API-driven data services
GenAI, agentic systems
MLOps, MLOps workflows
Apache Spark
NoSQL
Agile Methodology

Benefits

Health insurance, dental insurance, vision insurance
Long term and short term disability insurance
Employee assistance program
Flexible spending account
Life insurance
Generous time off policies, including:
- 4-12 weeks fully paid parental leave based on tenure
- 11 paid holidays
- Additional flexible paid vacation and sick leave (US benefits overview)

Preferred Certifications