Analytics Engineer Upto 25 hr
Data & Analytics
WFA Digital Insight
The demand for skilled analytics engineers has skyrocketed, with a 25% increase in job openings in the past year alone. As companies like Mercor pioneer AI research, the need for experts who can navigate complex data landscapes has never been more pressing. With the shift to remote work, candidates with strong digital skills and experience in data engineering are in high demand. Mercor's commitment to innovation and its impressive roster of investors make this role a compelling opportunity for those looking to make a meaningful impact. Before applying, candidates should be prepared to showcase their expertise in dbt model development, pipeline orchestration, and data quality testing.
Job Description
About the Role
As an Analytics Engineer at Mercor, you will play a critical role in developing and maintaining the company's data infrastructure, working closely with leading AI research labs to drive innovation and growth. Your day-to-day will involve designing and implementing ETL/ELT pipelines, developing dbt models, and creating Airflow/Dagster DAGs to ensure seamless data flow. You will be an integral part of a team that values collaboration, creativity, and a passion for data-driven decision making.Mercor's mission is to connect elite creative and technical talent with cutting-edge AI research labs, and as an Analytics Engineer, you will be at the forefront of this effort. With a strong foundation in data engineering and analytics, you will be empowered to work independently, tackling complex challenges and developing innovative solutions.
The company's vision is to create a future where human potential is amplified by AI, and as an Analytics Engineer, you will be a key contributor to this vision. You will have the opportunity to work with a talented team of engineers, researchers, and industry experts, sharing knowledge, expertise, and best practices to drive success.
What You Will Do
- Build long-horizon pipeline tasks with deterministic rubrics to grade agent performance against verifiable ground truth
- Develop ETL/ELT pipelines and dbt models to produce specified output tables with incremental logic and defined watermark behavior
- Create Airflow/Dagster DAGs that pass test suites and data quality tests with known pass/fail cases
- Design warehouse schemas matching defined contracts and performance targets tied to measured query-time budgets
- Work independently in long focus sessions to create challenging scenarios for agent evaluation
- Ensure tasks have checkable answers without open-ended essays or subjective judgment calls
- Collaborate with cross-functional teams to identify and prioritize data engineering projects
- Develop and maintain data quality tests and validation procedures to ensure data accuracy and reliability
- Stay up-to-date with industry trends and emerging technologies in data engineering and analytics
What We Are Looking For
- BS or MS in Computer Science or a related field
- 3+ years of experience in data engineering or analytics engineering
- Expertise in dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), and data quality and testing
- Comfortable with data engineering artifacts: dbt models, DAGs, schema docs, data contracts, and test suites
- Clear written communication skills to articulate reasoning and encode it into deterministic rubrics
- Experience working with remote teams and collaborating with stakeholders across different time zones
- Strong problem-solving skills and attention to detail
- Ability to work in a fast-paced environment and adapt to changing priorities
Nice to Have
- Experience with cloud-based data platforms (AWS, GCP, Azure)
- Familiarity with machine learning and AI technologies
- Knowledge of data governance and data security best practices
- Experience with agile development methodologies and version control systems (Git, SVN)
Benefits and Perks
- Competitive hourly rate ($90-25/hour)
- Opportunity to work with leading AI research labs and contribute to cutting-edge projects
- Collaborative and dynamic work environment with a team of talented engineers and researchers
- Flexible working hours and remote work arrangements
- Professional development opportunities and access to industry conferences and training
- Access to a network of elite creative and technical talent
- Recognition and rewards for outstanding performance and contributions
- Comprehensive benefits package, including health insurance and retirement planning
- Generous paid time off and holiday policy
- State-of-the-art technology and tools to support your work
- Opportunity to work on high-impact projects and make a meaningful difference in the industry
How to Stand Out
- Be prepared to showcase your expertise in dbt model development, pipeline orchestration, and data quality testing, and provide specific examples of your experience in these areas.
- Highlight your ability to work independently and collaboratively as part of a remote team, and demonstrate your strong problem-solving skills and attention to detail.
- Make sure to review the company's website and familiarize yourself with their mission, values, and current projects to demonstrate your interest and enthusiasm for the role.
- Develop a strong understanding of the company's technology stack and be prepared to discuss your experience with similar tools and platforms.
- Be prepared to provide examples of your experience working with remote teams and collaborating with stakeholders across different time zones.
- Showcase your ability to communicate complex technical concepts clearly and effectively, and demonstrate your strong written and verbal communication skills.
- Be prepared to discuss your experience with data governance and data security best practices, and demonstrate your ability to work in a fast-paced environment and adapt to changing priorities.
This is a remote position listed on WFA Digital, the platform for professionals who work from anywhere. Browse more remote jobs across all categories.
WFA Digital Insight
The demand for skilled analytics engineers has skyrocketed, with a 25% increase in job openings in the past year alone. As companies like Mercor pioneer AI research, the need for experts who can navigate complex data landscapes has never been more pressing. With the shift to remote work, candidates with strong digital skills and experience in data engineering are in high demand. Mercor's commitment to innovation and its impressive roster of investors make this role a compelling opportunity for those looking to make a meaningful impact. Before applying, candidates should be prepared to showcase their expertise in dbt model development, pipeline orchestration, and data quality testing.
Job Description
About the Role
As an Analytics Engineer at Mercor, you will play a critical role in developing and maintaining the company's data infrastructure, working closely with leading AI research labs to drive innovation and growth. Your day-to-day will involve designing and implementing ETL/ELT pipelines, developing dbt models, and creating Airflow/Dagster DAGs to ensure seamless data flow. You will be an integral part of a team that values collaboration, creativity, and a passion for data-driven decision making.Mercor's mission is to connect elite creative and technical talent with cutting-edge AI research labs, and as an Analytics Engineer, you will be at the forefront of this effort. With a strong foundation in data engineering and analytics, you will be empowered to work independently, tackling complex challenges and developing innovative solutions.
The company's vision is to create a future where human potential is amplified by AI, and as an Analytics Engineer, you will be a key contributor to this vision. You will have the opportunity to work with a talented team of engineers, researchers, and industry experts, sharing knowledge, expertise, and best practices to drive success.
What You Will Do
- Build long-horizon pipeline tasks with deterministic rubrics to grade agent performance against verifiable ground truth
- Develop ETL/ELT pipelines and dbt models to produce specified output tables with incremental logic and defined watermark behavior
- Create Airflow/Dagster DAGs that pass test suites and data quality tests with known pass/fail cases
- Design warehouse schemas matching defined contracts and performance targets tied to measured query-time budgets
- Work independently in long focus sessions to create challenging scenarios for agent evaluation
- Ensure tasks have checkable answers without open-ended essays or subjective judgment calls
- Collaborate with cross-functional teams to identify and prioritize data engineering projects
- Develop and maintain data quality tests and validation procedures to ensure data accuracy and reliability
- Stay up-to-date with industry trends and emerging technologies in data engineering and analytics
What We Are Looking For
- BS or MS in Computer Science or a related field
- 3+ years of experience in data engineering or analytics engineering
- Expertise in dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), and data quality and testing
- Comfortable with data engineering artifacts: dbt models, DAGs, schema docs, data contracts, and test suites
- Clear written communication skills to articulate reasoning and encode it into deterministic rubrics
- Experience working with remote teams and collaborating with stakeholders across different time zones
- Strong problem-solving skills and attention to detail
- Ability to work in a fast-paced environment and adapt to changing priorities
Nice to Have
- Experience with cloud-based data platforms (AWS, GCP, Azure)
- Familiarity with machine learning and AI technologies
- Knowledge of data governance and data security best practices
- Experience with agile development methodologies and version control systems (Git, SVN)
Benefits and Perks
- Competitive hourly rate ($90-25/hour)
- Opportunity to work with leading AI research labs and contribute to cutting-edge projects
- Collaborative and dynamic work environment with a team of talented engineers and researchers
- Flexible working hours and remote work arrangements
- Professional development opportunities and access to industry conferences and training
- Access to a network of elite creative and technical talent
- Recognition and rewards for outstanding performance and contributions
- Comprehensive benefits package, including health insurance and retirement planning
- Generous paid time off and holiday policy
- State-of-the-art technology and tools to support your work
- Opportunity to work on high-impact projects and make a meaningful difference in the industry
How to Stand Out
- Be prepared to showcase your expertise in dbt model development, pipeline orchestration, and data quality testing, and provide specific examples of your experience in these areas.
- Highlight your ability to work independently and collaboratively as part of a remote team, and demonstrate your strong problem-solving skills and attention to detail.
- Make sure to review the company's website and familiarize yourself with their mission, values, and current projects to demonstrate your interest and enthusiasm for the role.
- Develop a strong understanding of the company's technology stack and be prepared to discuss your experience with similar tools and platforms.
- Be prepared to provide examples of your experience working with remote teams and collaborating with stakeholders across different time zones.
- Showcase your ability to communicate complex technical concepts clearly and effectively, and demonstrate your strong written and verbal communication skills.
- Be prepared to discuss your experience with data governance and data security best practices, and demonstrate your ability to work in a fast-paced environment and adapt to changing priorities.
This is a remote position listed on WFA Digital, the platform for professionals who work from anywhere. Browse more remote jobs across all categories.