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Data Engineer

About HighLevel:

HighLevel is a cloud-based, all-in-one white-label marketing and sales platform that empowers marketing agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. With a focus on streamlining marketing efforts and providing comprehensive solutions, HighLevel helps businesses of all sizes achieve their marketing goals. We currently have ~1200 employees across 15 countries, working remotely as well as in our headquarters, which is located in Dallas, Texas. Our goal as an employer is to maintain a strong company culture, foster creativity and collaboration, and encourage a healthy work-life balance for our employees wherever they call home.


Our Website - https://www.gohighlevel.com/

YouTube Channel - https://www.youtube.com/channel/UCXFiV4qDX5ipE-DQcsm1j4g

Blog Post https://blog.gohighlevel.com/general-atlantic-joins-highlevel/


Our Customers:

HighLevel serves a diverse customer base, including over 60K agencies & entrepreneurs and 500K businesses globally. Our customers range from small and medium-sized businesses to enterprises, spanning various industries and sectors.


Scale at HighLevel:

We operate at scale, managing over 40 billion API hits and 120 billion events monthly, with more than 500 micro-services in production. Our systems handle 200+ terabytes of application data and 6 petabytes of storage.


About the Role:

We are seeking a talented and motivated data engineer to join our team who will be responsible for designing, developing, and maintaining our data infrastructure and developing backend systems and solutions that support real-time data processing, large-scale event-driven architectures, and integrations with various data systems. This role involves collaborating with cross-functional teams to ensure data reliability, scalability, and performance. The candidate will work closely with data scientists, analysts and software engineers to ensure efficient data flow and storage, enabling data-driven decision-making across the organisation.


Responsibilities:
  • Software Engineering Excellence: Write clean, efficient, and maintainable code using JavaScript or Python while adhering to best practices and design patterns
  • Design, Build, and Maintain Systems: Develop robust software solutions and implement RESTful APIs that handle high volumes of data in real-time, leveraging message queues (Google Cloud Pub/Sub, Kafka, RabbitMQ) and event-driven architectures
  • Data Pipeline Development: Design, develop and maintain data pipelines (ETL/ELT) to process structured and unstructured data from various sources
  • Data Storage & Warehousing: Build and optimize databases, data lakes and data warehouses (e.g. Snowflake) for high-performance querying
  • Data Integration: Work with APIs, batch and streaming data sources to ingest and transform data
  • Performance Optimization: Optimize queries, indexing and partitioning for efficient data retrieval
  • Collaboration: Work with data analysts, data scientists, software developers and product teams to understand requirements and deliver scalable solutions
  • Monitoring & Debugging: Set up logging, monitoring, and alerting to ensure data pipelines run reliably
  • Ownership & Problem-Solving: Proactively identify issues or bottlenecks and propose innovative solutions to address them


Requirements:
  • 3+ years of experience in software development
  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
  • Strong Problem-Solving Skills: Ability to debug and optimize data processing workflows
  • Programming Fundamentals: Solid understanding of data structures, algorithms, and software design patterns
  • Software Engineering Experience: Demonstrated experience (SDE II/III level) in designing, developing, and delivering software solutions using modern languages and frameworks (Node.js, JavaScript, Python, TypeScript, SQL, Scala or Java)
  • ETL Tools & Frameworks: Experience with Airflow, dbt, Apache Spark, Kafka, Flink or similar technologies
  • Cloud Platforms: Hands-on experience with GCP (Pub/Sub, Dataflow, Cloud Storage) or AWS (S3, Glue, Redshift)
  • Databases & Warehousing: Strong experience with PostgreSQL, MySQL, Snowflake, and NoSQL databases (MongoDB, Firestore, ES)
  • Version Control & CI/CD: Familiarity with Git, Jenkins, Docker, Kubernetes, and CI/CD pipelines for deployment
  • Communication: Excellent verbal and written communication skills, with the ability to work effectively in a collaborative environment
  • Experience with data visualization tools (e.g. Superset, Tableau), Terraform, IaC, ML/AI data pipelines and devops practices are a plus


EEO Statement:

The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.


#LI-Remote #LI-NJ1

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Average salary estimate

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What You Should Know About Data Engineer, highlevel

HighLevel is seeking a passionate Data Engineer to join our dynamic team in Delhi! As our Data Engineer, you'll play a crucial role in designing, developing, and maintaining our data infrastructure, creating backend systems that support real-time data processing and large-scale event-driven architectures. We pride ourselves on fostering creativity and collaboration, making this a fantastic opportunity to work alongside talented data scientists, analysts, and engineers. You'll be responsible for writing clean, maintainable code, developing data pipelines, optimizing databases, and ensuring data reliability and scalability. With a diverse customer base of over 60,000 agencies and 500,000 businesses globally, your work will directly impact our mission to empower organizations to achieve their marketing goals. If you have a strong background in software development, cloud platforms, and database management, coupled with a knack for problem-solving, we want to hear from you! At HighLevel, you can expect a supportive company culture, opportunities for professional growth, and the chance to be part of a forward-thinking team that’s always pushing boundaries. Join us in shaping the future of digital marketing solutions!

Frequently Asked Questions (FAQs) for Data Engineer Role at highlevel
What are the primary responsibilities of a Data Engineer at HighLevel?

At HighLevel, a Data Engineer is responsible for designing and maintaining our data infrastructure, developing data pipelines, and ensuring the reliability and performance of data systems. You will collaborate with cross-functional teams to create effective solutions that support real-time data processing and large-scale architectures.

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What qualifications do I need to become a Data Engineer at HighLevel?

To be a successful Data Engineer at HighLevel, you should have at least 3 years of experience in software development, along with a Bachelor's or Master's degree in Computer Science or related fields. A strong understanding of programming languages like JavaScript or Python, as well as hands-on experience with cloud platforms and data warehousing, is essential.

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What technologies are commonly used by Data Engineers at HighLevel?

Data Engineers at HighLevel frequently work with technologies such as Google Cloud Platform, PostgreSQL, Snowflake, as well as ETL tools like Apache Spark and Airflow. Familiarity with message queues and version control systems will also be beneficial in this role.

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How does collaboration work for Data Engineers at HighLevel?

Collaboration is key at HighLevel! As a Data Engineer, you'll work closely with data scientists, analysts, and software developers to understand requirements and deliver scalable solutions that drive data-driven decision-making across the organization.

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What is the company culture like at HighLevel for Data Engineers?

At HighLevel, we pride ourselves on a strong company culture that emphasizes creativity, teamwork, and a healthy work-life balance. As a Data Engineer, you will be part of a supportive environment that encourages collaboration and innovation.

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Common Interview Questions for Data Engineer
Can you explain your experience with writing ETL processes?

When answering about ETL processes, highlight specific projects where you've designed and implemented ETL pipelines, detailing the tools you used, such as Apache Airflow or Apache Spark, and how you overcame challenges in data integration.

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What programming languages are you proficient in and how have you used them as a Data Engineer?

Discuss your proficiency in languages like Python or JavaScript and provide examples of projects where you've utilized these languages to solve data-related problems or improve workflows within your team.

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How do you ensure data quality and integrity in your pipelines?

Emphasize the methods you use for data validation, monitoring, and logging throughout your data pipelines to identify and resolve issues, ensuring that the data delivered is both accurate and timely.

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Describe a challenging data problem you faced and how you solved it.

Use the STAR method to answer this question. Describe the Situation, Task, Action, and Result, focusing on how your technical skills and problem-solving abilities led to a successful outcome.

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What experience do you have with cloud platforms for data storage?

Discuss your experience with platforms such as Google Cloud Platform and AWS, mentioning specific services like Google Cloud Storage or AWS Redshift and how you utilized them to store and manage large datasets.

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How would you optimize a slow-running SQL query?

Talk about techniques like indexing, query rewriting, and partitioning, demonstrating your SQL knowledge and showing your analytical skills in optimizing database performance.

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What tools or frameworks have you used for real-time data processing?

Mention technologies such as Kafka or Google Cloud Pub/Sub, providing examples of how you've implemented these tools in previous roles to support real-time data streams.

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How do you manage version control in your projects?

Explain your familiarity with Git and how you implement it in your workflows, including branching strategies, commit practices, and collaboration with team members during development cycles.

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Can you explain your experience with data visualization tools?

Detail your experience with tools like Tableau or Superset, and give an example of how you've used them to present data insights to stakeholders or drive decisions within your organization.

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What strategies do you use for debugging data pipelines?

Discuss your approach to identifying and resolving issues in data pipelines, including logging, monitoring, and automated alerting to proactively manage data flows and fix problems quickly.

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Full-time, remote
DATE POSTED
March 21, 2025

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