Kforce has a client in Erlanger, KY that is seeking a Data Engineer.
Responsibilities
Design, build, refactor, and maintain data pipelines using Microsoft Azure, SQL, Azure Data Factory, Azure Synapse, Databricks, Python, and PySpark to meet business requirements for reporting, analysis, and data science
Teach, adhere to, and contribute to DataOps and MLOps standards and best practices to accelerate and continuously improve data system performance
Design, and integrate fault tolerance and enhancements into data pipelines to improve quality and performance
Perform root cause analysis and solve problems using analytical and technical skills to optimize data delivery and reduce costs
Mentor more junior Data Engineers
REQUIREMENTS:
Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology or equivalent combination of data engineering professional experience and education
Certifications from cloud providers (e.g., Azure Certified Solutions Architect, Azure Data Engineer) can be advantageous
Certifications such as Databricks Certified Associate Developer for Apache Spark or Databricks Certified Professional Data Scientist
3+ years proven Data Engineering experience
Experience with Microsoft Azure, SQL, Azure Data Factory, Azure Synapse, Databricks, Python, PySpark, SAP Datasphere, Power BI or other cloud-based data systems
Experience with Azure DevOps, GitHub, CI/CD
Experience with database storage systems such as cloud, relational, mainframe, data lake, and data warehouse
Experience building cloud ETL pipelines using code or ETL platforms utilizing database connections, APIs, or file-based
Experience with data warehousing concepts and agile methodology
Experience designing and coding data manipulations applying processing techniques to extract value from large, disconnected datasets
Demonstrates continuous learning to upskill data engineering techniques and business acumen
Experience with Databricks: Hands-on experience with Databricks, including familiarity with its architecture, features, and services
Proficiency in Spark: Strong knowledge of Apache Spark, including Spark SQL, Spark Streaming, and Spark MLlib, as Databricks is built on Spark
Programming Languages: Proficiency in programming languages commonly used in data engineering such as Python, Scala, SQL, and Java
Experience with data warehousing concepts, ETL processes, and tools like Apache Airflow, Talend, or Informatica
Knowledge of relational and NoSQL databases, data modeling, and query optimization
Familiarity with big data technologies and ecosystems, including Hadoop, Hive, and Kafka
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless
and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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