- Design and implement scalable and reliable data pipelines to ingest, process, and store diverse data at scale, using technologies such as Apache Spark, Hadoop, and Kafka.
- Work within cloud environments like AWS or Azure to leverage services including but not limited to EC2, RDS, S3, Lambda, and Azure Data Lake for efficient data handling and processing.
- Develop and optimize data models and storage solutions (SQL, NoSQL, Data Lakes) to support operational and analytical applications, ensuring data quality and accessibility.
- Utilize ETL tools and frameworks (e.g., Apache Airflow, Talend) to automate data workflows, ensuring efficient data integration and timely availability of data for analytics.
- Collaborate closely with data scientists, providing the data infrastructure and tools needed for complex analytical models, leveraging Python or R for data processing scripts.
- Ensure compliance with data governance and security policies, implementing best practices in data encryption, masking, and access controls within a cloud environment.
- Monitor and troubleshoot data pipelines and databases for performance issues, applying tuning techniques to optimize data access and throughput.
- Stay abreast of emerging technologies and methodologies in data engineering, advocating for and implementing improvements to the data ecosystem.
- Bachelor's degree in computer science, MIS, or other business discipline or equivalent combination of education and/or experience.
- 8+ years of experience in data engineering, with a proven track record in designing and operating large-scale data pipelines and architectures.
- Strong experience in AWS and Azure cloud services, with hands-on experience in integrating cloud storage and compute services with Databricks.
- Expertise in developing ETL/ELT workflows.
- Comprehensive knowledge of platforms and services like Databricks, Dataiku, and AWS native
- data offerings
- Solid experience with big data technologies (Apache Spark, Hadoop, Kafka) and cloud services (AWS, Azure) related to data processing and storage.
- Proficient in SQL and programming languages relevant to data engineering (Python, Java, Scala).
- Hands on RDBMS experience (data modeling, analysis, programming, stored procedures)
- Familiarity with machine learning model deployment and management practices is a plus.
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Senior Data Engineer - Crockett, United States - Vaco
Description
***Senior Data Engineer***
All the relevant skills, qualifications and experience that a successful applicant will need are listed in the following description.***Onsite in Houston TX-77077***
Job Summary
The Senior Data Engineer plays a crucial role in architecting, implementing, and managing robust, scalable data infrastructures.
This position demands a blend of systems engineering, data integration, and data analytics skills to enhance a company's data capabilities, supporting advanced analytics, machine learning projects, and real-time data processing needs.
Responsibilities:
Minimum Qualifications
Certificates, Licenses, Registrations:
Preferred: Databricks Certified Associate Developer for Apache Spark, AWS Certified Solutions Architect, Azure Data Engineer Associate, or other relevant certifications.
