Data Quality/ETL Specialist - FULLY REMOTE - Employee in USD
WFA Digital Insight
The demand for skilled Data Quality/ETL Specialists has surged in recent years, with over 25% of companies investing in data quality initiatives. As remote work continues to rise, roles like this one offer a unique blend of technical expertise and flexibility. With the current job market favoring candidates with strong digital skills, this position stands out for its requirement of MEAN stack framework experience and data quality tools. As a candidate, it's essential to understand the company's commitment to agile methodologies and the importance of data-driven decision-making. Before applying, consider your experience with ETL pipeline design, data cleansing methods, and large-scale messaging technologies like Kafka.
Job Description
About the Role
As a Data Quality/ETL Specialist, you will be working with an agile team to design and implement ETL processes that ensure the accuracy and quality of data loaded into the data lakehouse. This role is critical to the organization's data-driven decision-making and requires a strong understanding of data quality measures and ETL testing. You will be working closely with the development team to translate design specifications and functional requirements into ETL processes.The team is looking for a collaborative and skilled specialist who can work effectively in a remote setting, with a strong focus on delivering high-quality results. The ideal candidate will have experience working with AWS ETL and data quality tools, as well as a solid understanding of data cleansing and deduplication methods.
What You Will Do
- Design and implement ETL processes using MEAN stack framework
- Translate design specifications and functional requirements into ETL processes
- Develop data import, transformation, and loading processes to data lakehouse from MongoDB
- Merge code into shared repositories, validate code, and perform quality assurance
- Implement data quality measures to ensure accuracy of data loaded into data lakehouse
- Profile and analyze data to identify trends and patterns
- Collaborate with the development team to ensure seamless integration of ETL processes
- Develop and maintain documentation of ETL processes and data quality measures
- Participate in agile team meetings and contribute to the development of the team's goals and objectives
What We Are Looking For
- At least 2 years of experience working with AWS ETL and data quality tools
- Experience designing and implementing ETL pipelines
- Strong understanding of data cleansing and deduplication methods
- Experience with MEAN stack framework
- Experience with ensuring data accuracy and ETL testing
- Experience with Kafka or other similar large-scale messaging technologies
- Knowledge and understanding of SDLC and Agile/Scrum procedures, CI/CD and Automation
- Fluent in English
- Ability to work 4-6 hours per day in the normal office hours of New York, US
Nice to Have
- Experience with data lakehouse architecture and design
- Knowledge of data governance and data quality best practices
- Familiarity with cloud-based data platforms and tools
- Certification in data quality or related field
Benefits and Perks
- Attractive salary package
- Opportunity to work with a global organization
- Flexible remote work arrangement
- Professional development and growth opportunities
- Access to cutting-edge tools and technologies
- Collaborative and dynamic team environment
- Recognition and reward for outstanding performance
- Comprehensive benefits package, including health insurance and retirement plan
How to Stand Out
- Tip: Make sure to highlight your experience with MEAN stack framework and data quality tools in your resume and cover letter.
- When applying, be prepared to provide examples of your experience with ETL pipeline design and data cleansing methods.
- To stand out, consider including a portfolio of your work, such as examples of ETL processes you've designed and implemented.
- In the interview, be prepared to discuss your understanding of data quality measures and ETL testing, as well as your experience with agile methodologies.
- When negotiating salary, be sure to research the market rate for Data Quality/ETL Specialists in the US and be prepared to make a strong case for your worth.
- Be cautious of companies that do not provide clear information about their data quality initiatives or ETL processes, as this may indicate a lack of investment in data-driven decision-making.
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