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Sr. Data Engineer

At WISEcode, we're a well-funded, dynamic startup. WISEcode makes personalized nutrition a reality based on the facts – what truly is in our food — and marries this data with your preferences. Powered by AI and the world’s best food and nutrition database, WISEcode embraces the fact that we are all different, have different dietary needs, objectives, and preferences, and should not be at the mercy of market spin or “expert” opinion. Every one of us should have the information we need to make the best decisions for ourselves.


We are seeking for a skilled Sr. Data Engineer to join us in a groundbreaking initiative at the intersection of data engineering, machine learning, and proprietary nutrition. In this role, you will play a key part in shaping the future of wellness by developing an innovative nutrition database. Join a company with ambitious goals, aiming for a multi-billion USD valuation while making a meaningful and lasting impact on health and wellness.


As a Sr. Data Engineer, you will be tasked with designing, developing, testing, and maintaining systems that enable the acquisition, storage, processing, and retrieval of data for analytics, machine learning, and various applications. You will collaborate closely with data scientists, application developers, and machine learning engineers to understand their data requirements and ensure the delivery of a robust and efficient data pipeline. In this role, you'll focus on building scalable, high-performance data infrastructures while ensuring data is highly available, reliable, and optimized for business insights. You will also play a key role in implementing best practices for data management, security, and governance.


Key Responsibilities:

Collaborate with product teams and business stakeholders to gather data requirements Participate in sprint planning, backlog grooming, and other agile activities to align with project goals and technical specifications.

Work closely with cross-functional teams to understand project dependencies and ensure smooth execution of data engineering deliverables.

Design, develop, and maintain the organization’s data infrastructure, including data platforms, databases, and analytics tools, while ensuring compliance with data governance and security best practices (e.g., GDPR).

Build and maintain scalable data pipelines for data ingestion, transformation, and storage, optimizing performance and reliability.

Implement data engineering solutions to prepare analytics-ready datasets for analysis and reporting.

Build data models to support various consumption patterns, ensuring efficient data access for different use cases.

Build feature engineering pipelines to integrate machine learning algorithms into the data ecosystem. Integrate machine learning models with data pipelines for seamless deployment and scalability.

Implement data quality checks, validation rules, and cleansing processes to ensure accuracy.

Maintain documentation for platform architecture, data models, data engineering processes, and data lineage.

Participate in Data Operations ensuring adherence to SLA and data quality standards.


Qualifications:

7+ years of combined experience in data engineering, data warehousing, and data science.

Bachelor’s degree in Computer Science, Engineering, or equivalent work experience (Master’s degree preferred.

Expertise in data modeling, ETL processes, and data warehousing concepts.

Strong proficiency in programming languages such as Python and Scala.

Experience with big data technologies and frameworks like Hadoop and Spark

Hands-on experience with any of the major cloud providers (AWS, Google Cloud, Azure).

Proven experience building data lakes using Databricks, Snowflake, or AWS Redshift.

Databricks Data Engineering Professional certification is a strong plus.

Proficiency in SQL and relational databases such as SQL Server, PostgreSQL, and My SQL.

Experience developing data pipelines with technologies such as Airflow, Dagster, and Kafka.

Solid understanding of data security and privacy regulations.

Strong understanding of software development life cycle best practices, including test-driven development, continuous integration/deployment, and code security scanning.

Excellent problem-solving skills with a strong attention to detail, and the ability to adapt to evolving requirements.

Ability to navigate ambiguity and drive data engineering tasks to success without relying solely on formal authority.

Proven experience supporting data operations and managing SLAs in a production environment.

Outstanding communication and collaboration skills.

Ability to work independently and manage multiple tasks efficiently.

Positive, can-do attitude with a high-intensity work ethic and commitment to success.

Fast learner with the ability and interest to absorb new information, particularly in the nutrition domain.


Required Skills and Prior Experience:

5+years of experience in Python

5+ years of experience in SQL

5+ years of experience in PySpark

Implementing data engineering on Databricks

Hands-on experience with AWS tech stack

Working on PostgreSQL database

Developing data pipelines using frameworks such as Airflow/Dagster/Kafka

Building data models to structure the data to support various consumption patterns of the data (application consumption, analytics consumption etc.

Participating in agile methodologies for engineering project execution

Data access management and governance




$150,000 - $175,000 a year

Medical

Dental

Vision

401(k)

and other ancillary benefits offerings, along with Paid Time Off for vacation, illness, and other types of leave.


WISEcode is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, please send a request to WISEcode Human Resources at jobs@wisecode.ai.

Average salary estimate

$162500 / YEARLY (est.)
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max
$150000K
$175000K

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What You Should Know About Sr. Data Engineer, WISEcode

At WISEcode, we’re on a mission to revolutionize personalized nutrition, and we need a talented Sr. Data Engineer to help us pave the way! Our innovative startup blends cutting-edge AI technology with one of the world’s most comprehensive food and nutrition databases to empower individuals to make informed choices about their health. In this exciting role, you’ll play a crucial part in developing our unique nutrition database, collaborating with a dynamic team of data scientists and engineers. We’re looking for someone who’s not only skilled in data engineering but also passionate about harnessing data to make a real impact in wellness. You will design and maintain robust data infrastructures, ensuring our systems are optimized for performance and reliability. Your expertise will help shape the data pipeline for analytics and machine learning, creating a seamless flow of information that adds value to our products. You’ll work closely with product teams, participate in agile activities, and foster collaboration across departments as you address complex data challenges. At WISEcode, we value creativity and innovation; hence, we encourage you to implement best practices for data management and security. Interested in joining a company aiming for a multi-billion dollar valuation while making a significant difference? If you have 7+ years of relevant experience and a mastery of tools like Python, SQL, and big data frameworks, we’d love to hear from you! Come help us create exciting solutions filled with data-driven insights that lead to healthier decisions for everyone.

Frequently Asked Questions (FAQs) for Sr. Data Engineer Role at WISEcode
What are the responsibilities of a Sr. Data Engineer at WISEcode?

As a Sr. Data Engineer at WISEcode, your key responsibilities include designing, developing, testing, and maintaining the data infrastructure. You will collaborate closely with cross-functional teams to ensure smooth execution of data engineering deliverables, build and maintain scalable data pipelines, and implement best practices for data management and security. This role is crucial in supporting the development of our innovative nutrition database and analytics platforms.

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What qualifications do you need for the Sr. Data Engineer position at WISEcode?

To excel as a Sr. Data Engineer at WISEcode, you should have a minimum of 7 years of combined experience in data engineering and data warehousing. A bachelor’s degree in Computer Science or a related field is preferable, while a master’s degree is a plus. Proficiency in programming languages such as Python and SQL, along with experience in big data technologies, is essential.

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How does WISEcode support the career growth of a Sr. Data Engineer?

WISEcode is dedicated to fostering an environment that supports career growth for all employees, including Sr. Data Engineers. You’ll have access to ongoing training programs, mentorship opportunities, and the chance to work on innovative projects that enhance your skills. We encourage our employees to continually learn and adapt, especially in a rapidly evolving field like data engineering.

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What technologies should I be familiar with for the Sr. Data Engineer role at WISEcode?

As a Sr. Data Engineer at WISEcode, familiarity with tools and technologies such as Python, SQL, Databricks, AWS, and big data frameworks like Hadoop and Spark is crucial. Additionally, experience with data pipeline frameworks such as Airflow or Dagster will be beneficial. Understanding data governance and security practices is also essential.

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What can I expect from the work culture at WISEcode as a Sr. Data Engineer?

At WISEcode, you can look forward to a vibrant and collaborative work culture that values creativity and innovation. We embrace agile methodologies, encouraging open communication and teamwork across departments. As a Sr. Data Engineer, your insights and contributions will be valued, and you’ll find support from colleagues who are equally passionate about making a difference in the health and wellness industry.

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What is the salary range for a Sr. Data Engineer at WISEcode?

The salary range for the Sr. Data Engineer position at WISEcode is between $150,000 and $175,000 per year. In addition to a competitive salary, we offer a comprehensive benefits package, including medical, dental, vision insurance, a 401(k) plan, and generous paid time off. We aim to provide a supportive work environment where employees can thrive both personally and professionally.

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How does WISEcode ensure data quality in its engineering practices?

WISEcode implements strict data quality checks, validation rules, and cleansing processes as part of its data engineering practices. As a Sr. Data Engineer, you will play a key role in ensuring the accuracy and reliability of our data, which is paramount for our innovative nutrition solutions. We prioritize best practices in data management to uphold the high quality of our insights and offerings.

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Common Interview Questions for Sr. Data Engineer
Can you explain your experience with building scalable data pipelines?

In responding to this question, share specific projects where you designed data pipelines, highlighting the technologies you used, such as Airflow or Kafka. Discuss the challenges you faced and how you optimized for performance and reliability, demonstrating your hands-on experience and problem-solving skills.

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How do you approach data modeling for new projects?

When discussing your approach to data modeling, explain the steps you take to understand data requirements, visualize data flow, and design entities that serve various consumption patterns. It's essential to mention how you collaborate with stakeholders to align the model with business objectives.

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Describe a time when you ensured data governance in your previous work.

In your answer, recount a specific instance where you implemented or improved data governance protocols. Discuss the importance of regulations like GDPR and how you ensured compliance through thorough documentation, training, and establishing data access policies.

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What techniques do you use for ETL processes?

Here, you should elaborate on your experience with ETL techniques, mentioning tools you've used such as Talend or Informatica, and how you optimized the process for efficiency. Highlight your understanding of batch vs. real-time data processing and why it matters.

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How do you handle data quality issues?

Explain your strategy for addressing data quality issues, which might include implementing validation rules, performing regular audits, and using automated data cleansing tools. Provide examples from your previous roles where you successfully improved data quality standards.

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What experience do you have with big data technologies?

Discuss your familiarity with big data technologies such as Hadoop and Spark, including specific projects where you applied these tools to process large datasets. Talk about any challenges you faced and how you overcame them, demonstrating your technical prowess and adaptability.

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Why is documentation important in data engineering?

In your response, emphasize that documentation serves to maintain transparency, facilitate knowledge transfer, and assist in troubleshooting. Discuss how you incorporate documentation into your workflow, ensuring that your data engineering processes are well-documented for future reference.

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How do you prioritize tasks during a busy project?

To answer this question, highlight your methods for prioritization, such as using Agile methodologies, collaborating with stakeholders to understand project impact, and breaking down tasks into manageable parts. Share how you adapt to shifting priorities while maintaining project momentum.

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What is your experience with cloud platforms like AWS or Azure?

Provide examples of projects where you utilized cloud platforms, detailing the services you leveraged (like S3, Lambda, or Azure Data Lake). Talk about how you integrated cloud solutions within data architectures and the benefits these platforms brought to your workflow.

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How do you ensure the reliability of data systems?

In your answer, explain how you use monitoring tools, data backup strategies, and regular maintenance to ensure system reliability. Discuss any specific frameworks you've employed to oversee data integrity and accessibility and how you've adapted these practices to meet project demands.

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DATE POSTED
November 29, 2024

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