\nDescription\n\nWe are looking for an analytical, customer-focused and data-driven QA Analyst to join our team and optimize the quality and reliability of our data pipelines.\n\nOur data platform leverages vast datasets to provide actionable insights into healthcare prices, and supports decisions that influence the cost of care. As we continue to grow and pioneer a transparent healthcare ecosystem, we are looking for a Data Pipeline QA Analyst to be a part of our quest for transparency and change.\n\nTurquoise Health is on a transformative mission to revolutionize healthcare through price transparency. We are a dynamic, fully-remote team dedicated to making healthcare pricing clear and accessible, for consumers, providers, and payers alike. Our mission is to eliminate the financial complexity of healthcare. Join us, and be part of a team that's reshaping healthcare for the better.\n\nResponsibilities\n\nAs a QA Analyst at Turquoise Health, you will play a pivotal role in ensuring the integrity, reliability and quality of our data pipelines. Your work will directly contribute to our mission by maintaining the high quality of data that powers our platform.\n\nHere's what you can expect to do:\n\n\n* Develop and Execute Test Plans: Craft detailed test plans to validate the integrity of data pipelines and datasets. Your work will ensure the accuracy, completeness, and reliability of the data that our applications rely on.\n\n* Identify and Document Issues: Use your keen eye for detail to identify issues within our data pipelines. You'll document these findings and collaborate with our data engineering and data science teams to ensure timely resolution.\n\n* Perform Root Cause Analysis: When discrepancies arise, you'll dig deep to find the root cause. \n\n* Guide the Development of Automated Testing Frameworks: Leverage your findings to suggest enhancements to our automated testing frameworks.\n\n* Collaborate Across Teams: Work closely with cross-functional teams to understand data requirements and ensure that our data quality goals are met. \n\n* Contribute to Data Quality Policies: Play a key role in developing policies, standards, and procedures for data quality. \n\n\n\n\nHere's what you bring to the role\n\n\n* Technical Skills: You have 2+ years of experience in a data-focused role, and are highly proficient in SQL. Experience with Python is preferred. \n\n* Analytical Skills: Your exceptional analytical and problem-solving skills enable you to tackle complex issues. You have a keen attention to detail and a methodical approach to your work.\n\n* Collaboration: You are a team player with excellent communication skills. Your ability to work effectively in a remote team environment and collaborate across departments sets you apart.\n\n* Product Mindset: You are always looking for ways to iterate and improve upon processes and technologies. The end-user is always at the forefront of your mind and your decisions are guided by their needs. \n\n* Education/Experience: A Bachelorโs degree in STEM or a related field will equip you with the knowledge you need to excel in this role. Healthcare experience is a plus, but not required.\n\n\n\n\nSalary\n\nThe salary range for this full-time position is $80K - $90K. Our salary ranges are determined by role and level and reflect the minimum and maximum salary across all US locations (please note: salaries are location agnostic). Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. We will talk about compensation in our first conversation and be transparent throughout the process about which level we think is the best match for you in our organization. Please note that the salary range does not reflect total compensation, which includes base salary, benefits, and company stock options.\nBenefits\n\nCompetitive pay with equity options\n\nStellar health care plan options (Medical, Dental & Vision), with FSA, DCFSA, & HSA options\n\nCompany-sponsored disability & life insurance\n\nUnlimited PTO\n\n401(k) + 4% Matching\n\nFully remote work + flexible working hours\n\n$750 work-from-home setup budget \n\nPaid quarterly in-person co-working weeks\n\nQuarterly $150 co-hanging stipend to meet up with coworkers\n\nMonthly $100 health and wellness benefit\n\nGenerous paid family leave\n\nAnnual $1,200 learning & development stipend\n\n\n\n \n\n\n\n \n\n#Salary and compensation\n
No salary data published by company so we estimated salary based on similar jobs related to Python and Python jobs that are similar:\n\n
$60,000 — $100,000/year\n
\n\n#Benefits\n
๐ฐ 401(k)\n\n๐ Distributed team\n\nโฐ Async\n\n๐ค Vision insurance\n\n๐ฆท Dental insurance\n\n๐ Medical insurance\n\n๐ Unlimited vacation\n\n๐ Paid time off\n\n๐ 4 day workweek\n\n๐ฐ 401k matching\n\n๐ Company retreats\n\n๐ฌ Coworking budget\n\n๐ Learning budget\n\n๐ช Free gym membership\n\n๐ง Mental wellness budget\n\n๐ฅ Home office budget\n\n๐ฅง Pay in crypto\n\n๐ฅธ Pseudonymous\n\n๐ฐ Profit sharing\n\n๐ฐ Equity compensation\n\nโฌ๏ธ No whiteboard interview\n\n๐ No monitoring system\n\n๐ซ No politics at work\n\n๐ We hire old (and young)\n\n
\n\n#Location\nAtlanta, Georgia, United States
๐ Please reference you found the job on Remote OK, this helps us get more companies to post here, thanks!
When applying for jobs, you should NEVER have to pay to apply. You should also NEVER have to pay to buy equipment which they then pay you back for later. Also never pay for trainings you have to do. Those are scams! NEVER PAY FOR ANYTHING! Posts that link to pages with "how to work online" are also scams. Don't use them or pay for them. Also always verify you're actually talking to the company in the job post and not an imposter. A good idea is to check the domain name for the site/email and see if it's the actual company's main domain name. Scams in remote work are rampant, be careful! Read more to avoid scams. When clicking on the button to apply above, you will leave Remote OK and go to the job application page for that company outside this site. Remote OK accepts no liability or responsibility as a consequence of any reliance upon information on there (external sites) or here.