SME Data Engineer

I am Kishore from TechnoGen Inc looking for SME DATA Engineer for one of our clients. Below is the job description for your review.
Please let me know if you would be interested and share your updated resume.
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Title: SME DATA Engineer

Location: Ashburn VA

Job Type: Contract Hybrid

Duration: 12 Months

Job Description

Physical Requirements:

• The person in this position needs to occasionally move about inside the office to access file cabinets office machinery or to communicate with coworkers management and customers which may involve delivering presentations

Basic Qualifications:

• Experience with relational databases and knowledge of query tools and/or BI tools like Power BI or OBIEE and data analysis tools
• Extemsive experience with SQL and proficiency in writing complex queries.
• Solid understanding of data warehousing concepts and platforms such as Oracle and cloudbased solutions.
• Strong experience in automating ETL jobs via UNIX/LINUX shell scripts and CRON jobs.
• Demonstrate a strong practical understanding of data warehousing from a production relational database environment.
• Strong experience using analytic functions within Oracle or similar tools within nonrelational (MongoDB Cassandra etc.) database systems.
• Strong understanding of distributed computing principles and experience with frameworks like Apache Spark
• Handsonexperience with data lake architectures and technologies in a cloud environment.
• Experience with Atlassian suite of tools such as Jira and Confluence
• Knowledge of Continuous Integration & Continuous Development tools (CI/CD)
• Must be able to multitask efficiently and progressively and work comfortably in an everchanging data environment.
• Must work well in a team environment as well as independently.
• Excellent verbal/written communication and problemsolving skills; ability to communicate information to a variety of groups at different technical skill levels.

Preferred Qualifications:

• 5 years of experience in developing maintaining and optimizing complex Oracle PL/SQL packages to aggregate transactional data for consumption by data science/machine learning applications.
• 10 years of experience in working in data engineering with a focus on building and optimizing data pipelines and architectures. Must have full life cycle experience in design development deployment and monitoring.
• Experience with one or more relational database systems such as Oracle MySQL Postgres SQL server with heavy emphasis on Oracle.
• Extensive experience with cloud platforms (e.g. AWS Google Cloud etc) and cloudbased ETL/ELT tools.
• Experience with Amazon services such as S3 Redshift EMR and Scala.
• Experience with migrating onprem legacy database objects and data to the Amazon S3 cloud environment.
• Experience or familiarity with data science/machine learning and development experience for supervised and unsupervised learning with structure and unstructured datasets.
• Certifications in relevant technologies (e.g. AWS Certified Big Data Google Professional Data Engineer) are a plus.

Responsibilities include but are not limited to:

• Design develop and maintain scalable data pipelines and architectures to support data extraction transformation and loading (ETL/ELT) processes.
• Utilize strong SQL skills to perform complex data transformations and optimize database queries ensuring high performance and efficiency.
• Building comprehensive datasets by aggregating data sourced from various relational databases facilitating data analysts and data scientists in creating machine learning models reports and dashboards.
• Collaborate with crossfunctional teams (data analysts data scientists and business stakeholders) to understand business requirements and translate them into technical solutions.
• Assist with the implementation of data migration/pipelines from onprem to cloud/nonrelational storage platforms.
• Leverage distributed computing frameworks like Apache Spark to process large volume of data efficiently.
• Utilizing data analysis problemsolving investigative and creative thinking skills to handle extremely large datasets transforming them into various formats for diverse analytical products.
• Respond to data queries/analysis requests from various groups within an organization. Create and publish regularly scheduled and/or ad hoc reports as needed.
• Troubleshoot datarelated issues identify root causes and implement solutions to ensure data integrity and accuracy.
• implement best practices for data governance security and quality supporting the core business applications.
• Responsible for data engineering source code control using GitLab.