Data Engineer

LOCAL WA CANDIDATES ONLY

Hybrid work in South Seattle

$100-125K - Direct Hire

Benefits:

Opportunity to build, manage, and optimize data pipelines and move these effectively into production for key data and analytics consumers. Doing this in compliance with data governance and data security requirements while creating, improving, and operationalizing these integrated and reusable data pipelines. You will enable faster data access, integrated data reuse, and work to improve time-to-solution for organizational initiatives. You will work with across the business and with IT and other subject matter experts to plan and deliver optimal analytics and data solutions.

• Assist with building and maintaining data management systems that merge core data sources and accessible structures.
• Assist with architecting, creating, and maintaining data pipelines.
• Learn to use innovative and modern tools, techniques, and architectures to automate the most-common, repeatable and tedious data preparation and integration tasks.
• Assist with renovating the data management infrastructure to drive automation.
• Collaborate across teams and departments to refine data and data consumption requirements for various initiatives.
• Work to propose appropriate data ingestion, preparation, integration, and operationalization techniques to address data requirements.
• Perform data conversions, imports and exports of data within and between internal and external software systems.
• Develop programs to extract, transform, and load data between data sources.
• Create data transformation processes (ETL, SQL stored procedures, etc.) to support moderately complex to complex business systems and operational data flows.
• Deploy new software releases to customers strictly adhering to the Software Release Policy and providing detailed release notes document in due time for approval.
• Recommend and implement data reliability, efficiency, and quality improvements.
• Troubleshoot data analytic tools, systems, and software.
• Resolve production and development problems that relate to database management systems.
• Resolve conflicts between models; ensure data model consistency with the enterprise model (e.g., entity names, relationships and definitions).
• Assist in creating custom software components and analytics applications.
• Support appropriate use of provisioned data across the organization based on data governance and compliance policies, standards, and best practices.
• Promote the available data and analytics capabilities and inspire teams and leaders to leverage these capabilities to achieve their goals.

• Bachelor s degree in computer science, statistics, data management, information systems, information science, applied mathematics, or relevant work experience preferred.
• 2 or more years of relevant experience in Data Engineering, Database Administration, Data Analysis, or related work experience.
• ITIL certification required (or within 90 days of employment).
• Experience in data management disciplines including data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering preferred.
• Experience with popular databased programming languages (e.g., SQL, PL/SQL) for relational databases preferred.
• Experience working with large, heterogeneous datasets preferred.
• Experience working in an agile environment preferred.
• Experience in using engineering methodologies; related certification or professional engineer designation desirable.

Key Knowledge, Skills & Abilities:

• Deep knowledge of languages such as (R, Pearl, Python, Java, C++, C#, Scala, etc.).
• Knowledge of commercial data science platforms such as (Python, R, KNIME, Alteryx, etc.).
• Knowledge of modern data storage and access technologies, including caching, application of NoSQL, Key/Value, and RDBMS datastores.
• Deep knowledge of SQL, PL/SQL, Oracle.
• Knowledge of ETL processing and Change Data Capture (CDC) technologies.
• Knowledge of big data concepts, analysis, frameworks, API development, and visualization.
• Knowledge of streaming data technologies like Apache Spark, Flink and Kafka.
• Deep knowledge of business intelligence tools (such as Tableau, Qlik, PowerBI) and AI frameworks (Caffe, TensorFlow).
• Deep knowledge of Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management.
• Proven ability to clearly communicate technical concepts with stakeholders to increase their understanding and gain more value through data.
• Proven ability to use analytical skills to consider and incorporate the implications of analysis into recommendations for business decisions.
• Ability to leverage curiosity to identify and diagnose known and unknown problems.
• Proven ability to use data analysis skills to articulate and solve problems or answer questions with data.
• Ability to turn data insights into recommendations for both clients and internal stakeholders based on context.
• Advanced automation skills; strong data management, data analysis, API management, scripting, and visualization skills.