Data Engineer Manager

Envista Dentistry•Brea, CA

14h

About The Position

Develops or modifies program logic for new applications or software which may include coding, testing, debugging, documenting, implementing and maintaining software applications. Analyzes requirements, and maintains, tests and integrates application components. Programmer Analyst roles should be assigned to this job family. Accountabilities Design and implement scalable data pipelines for structured and unstructured data. Develop and maintain data models, integration frameworks, and storage solutions (cloud/on-prem/hybrid). Create scalable and reliable ETL/ELT processes to extract, transform, and load data from various sources into data warehouses or data lakes. Ensure adherence to data governance, security, and compliance standards (GDPR, HIPAA, SOX). Implement best practices for data quality, lineage, and metadata management. Define and maintain the overall data solution architecture, including integration patterns, data models, and governance frameworks. Collaborate with business stakeholders to translate requirements into technical designs that meet performance, security, and compliance standards. Oversee implementation of data platforms (e.g., cloud, on-premise, hybrid) ensuring scalability and interoperability. Establish and enforce architecture principles, standards, and best practices across development teams. Provide technical leadership during project lifecycle: design reviews, solution validation, and deployment strategies. Partner with IT security and compliance teams to embed security controls and regulatory adherence into all solutions. Evaluate emerging technologies and recommend adoption strategies aligned with enterprise goals. Clean, transform, and organize raw data from multiple sources into usable formats. Implement and enforce data quality, security, and governance policies, and ensure data is backed up and accessible. Work with data scientists, analysts, and stakeholders to understand business needs and provide data for analytics and decision-making. Evaluate and optimize existing data systems for improved performance, reliability, and speed. Create analytical tools and programs to help with data analysis and reporting. Partner with IT, BI, and business teams to translate requirements into technical solutions. Support advanced analytics initiatives by enabling reliable and accessible data infrastructure.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
5+ years of experience in data engineering.
Proven experience with ETL tools, cloud platforms (such as Azure, AWS, GCP), and big data technologies.
Strong understanding of enterprise data architecture, data modeling, and integration frameworks.
Knowledge of cloud platforms (e.g., Azure, AWS, GCP) and data services (e.g., Snowflake, Databricks).
Familiarity with compliance standards (GDPR, HIPAA, SOX) and security best practices.
Expertise in designing scalable data solutions using modern architectures (microservices, event-driven, API-first).
Proficiency in ETL/ELT tools, data warehousing, and big data technologies.
Proficiency in programming languages such as SQL and Python, experience with database systems, and familiarity with big data technologies.
Ability to lead architecture reviews and communicate complex technical concepts to non-technical stakeholders.
Strong problem-solving and analytical skills with experience in performance tuning and optimization.
Ability to communicate requirements and results with both technical and non-technical team members.

Responsibilities

Design and implement scalable data pipelines for structured and unstructured data.
Develop and maintain data models, integration frameworks, and storage solutions (cloud/on-prem/hybrid).
Create scalable and reliable ETL/ELT processes to extract, transform, and load data from various sources into data warehouses or data lakes.
Ensure adherence to data governance, security, and compliance standards (GDPR, HIPAA, SOX).
Implement best practices for data quality, lineage, and metadata management.
Define and maintain the overall data solution architecture, including integration patterns, data models, and governance frameworks.
Collaborate with business stakeholders to translate requirements into technical designs that meet performance, security, and compliance standards.
Oversee implementation of data platforms (e.g., cloud, on-premise, hybrid) ensuring scalability and interoperability.
Establish and enforce architecture principles, standards, and best practices across development teams.
Provide technical leadership during project lifecycle: design reviews, solution validation, and deployment strategies.
Partner with IT security and compliance teams to embed security controls and regulatory adherence into all solutions.
Evaluate emerging technologies and recommend adoption strategies aligned with enterprise goals.
Clean, transform, and organize raw data from multiple sources into usable formats.
Implement and enforce data quality, security, and governance policies, and ensure data is backed up and accessible.
Work with data scientists, analysts, and stakeholders to understand business needs and provide data for analytics and decision-making.
Evaluate and optimize existing data systems for improved performance, reliability, and speed.
Create analytical tools and programs to help with data analysis and reporting.
Partner with IT, BI, and business teams to translate requirements into technical solutions.
Support advanced analytics initiatives by enabling reliable and accessible data infrastructure.