Data Engineer

Job Description

Job Title:Data Engineer - ETL, Data Modeling, SQL, Cloud

Location: Omaha, Nebraska

Employee Status: Full-Time

Purpose:

Join our growing team in Omaha, Nebraska as a Data Engineer. You will play a crucial role in designing, developing, and maintaining our data architecture and pipelines. You will leverage your expertise in ETL/ELT processes, data modeling, and database technologies to ensure our data is accurate, accessible, and optimized for analysis. The ideal candidate possesses a strong understanding of data management, proficiency in tools like Informatica PowerCenter, and experience with cloud platforms.

Responsibilities:

Design, develop, and maintain efficient and scalable ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes using Informatica PowerCenter or other relevant data integration tools.

Utilize Informatica extensively for data integration, data transformation, and loading data from diverse sources (e.g., databases, APIs, cloud storage).

Collaborate with data scientists, data analysts, and business stakeholders to understand data requirements and design scalable and efficient data architectures optimized for Informatica.

Implement and maintain data models, database schemas, and structures within the Informatica environment and target database systems.

Optimize and troubleshoot Informatica workflows, mappings, and sessions for maximum performance and reliability.

Implement and enforce best practices for Informatica development, ensuring data quality, efficiency, and scalability.

Work extensively with various database systems, including MS SQL Server, Oracle, Snowflake, and potentially others.

Develop and manage large-scale databases within the Informatica ecosystem, ensuring data integrity, security, and performance.

Implement and maintain database solutions, including indexing, partitioning, query optimization, and performance tuning, leveraging Informatica capabilities.

Implement and enforce data quality standards, rules, and validation processes within the context of Informatica development.

Conduct thorough data testing and validation procedures using Informatica tools to ensure data accuracy, completeness, and consistency throughout the data pipelines.

Collaborate effectively with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand their data needs and deliver effective Informatica and data solutions.

Work closely with the IT team to integrate Informatica data solutions seamlessly into existing systems and infrastructure.

Create and maintain comprehensive technical documentation for Informatica data architectures, ETL/ELT processes, data models, and data flows.

Document data lineage, transformations, and dependencies within the Informatica environment for better understanding and maintainability.

Work Requirements, Experience, Education, and Skills:

Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field.

Minimum of 2 years of professional experience as a Data Engineer with a strong focus on Informatica PowerCenter development.

Solid understanding of core data management concepts, ETL/ELT methodologies, and various data modeling techniques (e.g., relational, dimensional).

Demonstrable proficiency in Informatica PowerCenter and other relevant Informatica tools and utilities.

Hands-on experience with relational database systems such as MS SQL Server, Oracle, and cloud-based data warehouses like Snowflake.

Proven experience with SQL for data querying, manipulation, and analysis.

Familiarity with scripting languages such as Python for data processing and automation.

Strong analytical, problem-solving, and critical-thinking skills with the ability to troubleshoot complex data issues.

Excellent verbal and written communication and interpersonal skills, with the ability to explain technical concepts to both technical and non-technical audiences.

Ability to actively participate in technical discussions and contribute to architectural decisions.

A proactive attitude and the ability to learn and adapt to new data technologies and tools quickly.

Full-time