Lead, Data Engineer

A LITTLE BIT ABOUT Boldr

• Boldr is the first global B-Corp dedicated to delivering world-class Client experiences while creating access to dignified, meaningful work in communities around the world.
• We are a global team, united by our desire to connect diverse people with common values for boldr impact. 
• We employ just over a thousand team members across five countries and we want to employ over 5,000 people by 2027, if not sooner.

LET'S START WITH OUR VALUES

• Meaningful connections start with AUTHENTICITY
• We do our best work by being CURIOUS
• We grow by remaining DYNAMIC
• Our success combines AMBITIOUS VISION with OPERATIONAL EXCELLENCE 
• At the heart of great partnerships we'll always find EMPATHY

As a Lead Data Engineer, you will build and guide the design, development, and optimization of complex data pipelines, ensuring that our data architecture aligns with business requirements. Your role encompasses both Boldr's internal data needs and our client data streams. You will ensure client data is securely loaded, meticulously cleaned, and readily available for our data analysts. This availability is essential for creating the dashboards and metrics that inform our clients on their business performance. 

You will also lead projects and build robust ETL processes, mentor junior engineers, and take ownership of the performance, security, and integrity of Boldr's data systems, working closely with stakeholders to identify opportunities for data-driven improvements and contribute to the strategic vision of our data platform.

We are currently looking for impact-driven individuals who are passionate in helping Boldr grow and achieve our Purpose. We expect our Team to become our ultimate partners to success by always giving their 110% in everything, sharing their talents and quirks, and championing our core values: Curious, Dynamic and Authentic.

• Mentorship and Leadership: Provide guidance and mentorship to Data Engineers, helping them navigate the organization's data domain and technology landscape through clear communication. Guide a team of data engineers, offering technical direction, mentorship, and conducting code reviews to ensure high-quality outcomes.
• Advanced Data Pipeline Design: Develop and optimize scalable ETL processes for both internal and client data needs.
• Data Architecture Enhancement: Identify opportunities to enhance data architecture for improved performance, scalability, and maintainability.
• Cross-Functional Collaboration: Work closely with stakeholders to understand data requirements and translate them into effective data solutions.
• Process Improvement: Automate manual processes, optimize data delivery, and redesign infrastructure for increased efficiency.
• Data Governance: Establish and maintain data quality, security, compliance, and accessibility standards across all data systems, ensuring adherence to best practices.
• Documentation and Standards: Develop comprehensive documentation for data standards, procedures, and definitions, ensuring a well-organized and consistent data ecosystem.
• Data Platform Leadership: Lead the design, development, and optimization of complex data pipelines, ensuring alignment with functional and non-functional business requirements.
• Cross-Domain Data Solutions: Identify, design, and execute solutions to complex data challenges across multiple domains, ensuring data integrity and high performance.
• Process Improvement: Drive internal process enhancements by automating manual tasks, optimizing data delivery, and redesigning infrastructure for improved scalability and reliability.
• Architecture Review Participation: Participate as a decision-maker and coach in architecture review processes, including Architecture Design Process sessions, to refine data architecture and system design.
• Stakeholder Collaboration: Represent the data and analytics teams as a domain expert, engaging with stakeholders to understand their evolving needs and translate them into technical requirements.
• Cross-functional Enablement: Unblock and empower team members across departments to effectively access and utilize data, ensuring smooth data flows throughout the organization.

• Curious: You explore new technologies, stay updated on industry trends, and ask the right questions.
• Dynamic: You adapt to changing priorities and thrive in fast-paced environments.
• Authentic: You communicate openly, provide constructive feedback, and build trust across teams.
• Collaborative: You work effectively with engineers, analysts, and stakeholders to deliver impactful solutions.
• Improvement-minded: You look for opportunities to automate, optimize, and enhance systems.
• Strategic and analytical: You can zoom out to understand the broader architecture while remaining hands-on in your work.
• Mentorship-oriented: You enjoy supporting engineers and fostering technical growth within the team.
  
  

• 6+ years in data engineering with a proven track record of designing and implementing scalable data architectures.
• 2+ years guiding or mentoring teams within data engineering, with experience leading complex data projects.
• 4+ years of experience with RESTful services, APIs, data pipelines, workflow management tools (e.g., Airflow, AWS), and databases such as Athena, Glue, Snowflake, and Postgres.
• Proficient in object-oriented and functional programming languages including Python, Java, C++, Scala, PHP, and others
• Deep expertise in data pipeline design, ETL/ELT processes, and data integration from diverse sources.
• Strong proficiency in SQL, Python, and big data technologies such as Apache Spark and Kafka, with extensive experience in working with relational databases, query authoring, and a solid understanding of various database systems
• Experience with cloud data platforms (e.g., AWS, GCP, Azure) and data warehousing technologies (e.g., Redshift, BigQuery, Snowflake).
• Hands-on experience with machine learning infrastructure, streaming data, advanced analytics, and working with unstructured datasets.
• Strong analytic skills related to working with unstructured datasets.
• Strong knowledge of data security and compliance best practices.
• Strategic and critical  thinker with a passion for data and its role in driving business decisions.
• Excellent communication and leadership skills.
• Able to balance hands-on technical work with high-level strategic planning.
• Continuously seeks opportunities for improvement and problem-solving.
• A collaborative leader who thrives in cross-functional environments and is committed to team growth.