Senior Data Engineer

Ascend Learning, LLC•Leawood, OR

1d•Remote

About The Position

As a Senior Data Engineer, you will be responsible for designing, building, and maintaining scalable and robust data pipelines and architectures. You will play a critical role in enabling data-driven decision-making by ensuring the availability, integrity, and performance of our data systems. You will work closely with business intelligence team, data scientists, and other stakeholders to support advanced analytics initiatives and contribute to our overall data strategy.

Requirements

High school diploma or GED required. Bachelor’s degree in computer science, software engineering, information technology, or a related field or relevant work experience preferred
6+ years of experience in a data engineering role with a strong focus on data warehousing and ETL processes
Skilled in SQL Server, MySQL, and Snowflake. Design data models, write SQL queries, and optimize database performance.
Experienced in building ETL pipelines using Azure Data Factory, SSIS, and Kafka for data integration and transformation.
Strong background in real-time data processing with Kafka and streaming technologies.
Knowledgeable in data warehouse design, data modeling, and database best practices.
Proficient in Python and Java for scripting and automating data workflows.
Hands-on experience with Azure Cloud Services like Azure Data Factory, Azure Databricks, and Azure SQL Database. Deploy and manage scalable data solutions on Azure.
Familiar with cloud infrastructure, automation, and security best practices to ensure reliable and secure data systems.
Understand data governance, data security, and compliance standards such as GDPR and HIPAA.
Strong problem-solving skills to quickly identify and fix data engineering issues.
Good communication skills to explain technical details clearly to both technical teams and business users.
Experience with RESTful APIs for integrating data systems.

Nice To Haves

Comfortable with additional programming languages like Scala and advanced Python.
Familiar with data visualization and BI tools to help deliver clear insights.

Responsibilities

Design and optimize complex data models, schemas, and storage structures across SQL Server, Snowflake, and other platforms to maximize performance, scalability, and data accessibility.
Lead the implementation and continuous improvement of enterprise-wide data warehouse strategies, ensuring data integrity, consistency, and alignment with organizational standards.
Design, develop, and maintain robust, scalable ETL/ELT pipelines leveraging SQL Server, Kafka, Azure Data Factory, Snowflake, and complementary technologies to support high-volume, real-time, and batch data processing.
Partner closely with business intelligence teams, data scientists, analysts, and key stakeholders to gather detailed requirements, translate them into scalable technical solutions, and deliver actionable data assets that drive business outcomes.
Collaborate with the data architecture team to define and implement scalable, high-performance data infrastructure and solutions aligned with enterprise data strategy.
Proactively monitor, troubleshoot, and optimize data pipelines and database systems to ensure high availability, reliability, and minimal latency, swiftly addressing any bottlenecks or failures.
Define, enforce, and champion data governance frameworks, ensuring compliance with data privacy regulations, security policies, and organizational standards.
Drive enhanced data observability by implementing comprehensive monitoring, logging, and alerting mechanisms to enable proactive identification and resolution of data quality and pipeline issues.
Stay abreast of emerging data engineering technologies, tools, and industry best practices to continuously innovate and improve data platform capabilities.
Provide technical leadership and mentorship to junior data engineers, fostering a culture of excellence, knowledge sharing, and adherence to best practices in data engineering and management.