About The Position | Major goals and objectives and location requirements
Dotdash Meredith is a leading digital media company that owns and operates a portfolio of highly respected brands across various verticals, including lifestyle, health, finance, and more. With a commitment to providing high-quality content and innovative digital experiences, Dotdash Meredith reaches millions of users globally and continues to drive growth and engagement across its platforms.
Dotdash Meredith is looking for a Senior Data Engineer with strong Python and SQL skills to join the Data Operations team. The successful candidate will help build our data integration pipelines that feed into our data lakes and warehouses while maintaining data quality and integrity in our data stores. We are looking for someone who is a great team player but can also work independently. This person will also work closely with key stakeholders and understand and implement business requirements and see to it that data deliverables are met.
Remote or Hybrid 3x a month
In-office Expectations: This position offers remote work flexibility; however, if you reside within a commutable distance to one of our offices in New York, Des Moines, Birmingham, Los Angeles, Chicago, or Seattle, the expectation is to work from the office three times per month
About The Positions Contributions:
Weight %
Accountabilities, Actions and Expected Measurable Results
60%
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You will enhance our systems by building new data integration pipelines and adding new data to our data lakes and warehouses while continuously optimizing them.
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You will work with internal team members as well as stakeholders to scope out business requirements and see data deliverables through to the end where they will be used via our Looker platform.
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You will continuously look for ways to improve our data transformations and data consumption processes so that our systems are running efficiently, and our customers are able to use and analyze our data quickly and effectively.
40%
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You will champion coding standards and best practices by actively participating in code reviews, and working to improve our internal tools and build process.
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You will work to ensure the security and stability of our infrastructure in a multi-cloud environment.
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You will collaborate with our Analytics engineers to ensure data integrity and the quality
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of our data deliverables.
The Role’s Minimum Qualifications and Job Requirements
Education:
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Degree in a quantitative field, such as computer science, statistics, mathematics, engineering, data science, or equivalent experience.
Experience:
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A minimum of 5+ years of experience in building and optimizing data pipelines with Python.
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You have experience writing complex SQL queries to analyze data.
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Window functions and nested subqueries are second nature to you.
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You have commendable experience with at least one cloud service platform (GCP and AWS preferred).
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You've worked with data at scale using Apache Spark, Beam or a similar framework.
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You're familiar with data streaming architectures using technologies like Pub/Sub and Apache Kafka.
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You are eager to learn about new tech stacks, big data technologies, data pipelining architectures, etc. and propose your findings to the team to try and optimize our systems.
Specific Knowledge, Skills, Certifications and Abilities:
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Strong Python and SQL skills.
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Experience with Google Cloud Platform is a plus.
% Travel Required (Approximate): 0%
