Find & Apply For Data Engineer Jobs In Hinds, Mississippi
Data Engineer jobs in Hinds, Mississippi involve managing, optimizing, and overseeing data systems. Professionals in this role collaborate with teams to ensure data accuracy and efficiency. Responsibilities include developing data pipelines, implementing ETL processes, and utilizing programming languages like Python and SQL. Below you can find different Data Engineer positions in Hinds, Mississippi.
Jobs in Hinds
Browse jobs from a variety of sources below, sorted with the most recently published, nearest to the top. Click the title to view more information and apply online.
Real-time Streaming Engineer – Flink
Eliassen Group
Hinds, MS
AI & Data Engineer
Cognizant Technology Solutions
Hinds, MS
Lead Data Engineer
Emergent Holdings
Hinds, MS
Data Engineer (Remote)
GovCIO
Hinds, MS
ETL Engineer (Remote)
GovCIO
Hinds, MS
Lead Data Engineer
Af - Group
Hinds, MS
Supervisor Data Engineering
Af - Group
Hinds, MS
HR Data Engineer
General Motors
Hinds, MS
Data Engineer
Cardinal Health
Hinds, MS
Data Engineer
Eliassen Group
Hinds, MS
Latest Jobs in Hinds
Salary Information & Job Trends In this Region
Data Engineers in Hinds, Mississippi, play a crucial role in managing and analyzing large datasets to drive business decisions and improve operational efficiencies. - Entry-level Data Engineer salaries range from $50,000 to $70,000 per year - Mid-career Data Analyst salaries range from $70,000 to $90,000 per year - Senior-level Data Architect salaries range from $90,000 to $120,000 per year The history of Data Engineers in Hinds, Mississippi, can be traced back to the rise of big data in the early 2000s, leading to increased demand for professionals with strong data management and analysis skills. As the field of data engineering has evolved, Data Engineers in Hinds, Mississippi, have adapted to new technologies and tools to handle massive amounts of data efficiently and effectively. Current trends in the field of Data Engineering in Hinds, Mississippi, include a shift towards cloud-based data storage and processing, the integration of machine learning and artificial intelligence into data analysis, and a focus on data security and privacy regulations to ensure compliance and protect sensitive information.