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WHAT IS YOUR ROLE:
As the Lead Data Engineer at Boldr, you will set up data pipeline architectures, extract data from various data sources, and provide ready-to-use datasets for our analytics team. You will be responsible for the extract, transform, load (ETL) process for all data from both Boldr and some of our clients. Additionally, you will ensure that all the databases under your supervision meet the performance, integrity, and security standards. You will support our growing analytics practice to generate insights for our ever-expanding client base.
WHY DO WE WANT YOU
We are currently in search of individuals driven by impact who are passionate about helping Boldr develop and achieve our Purpose. We expect our Team to be our essential partners in success by consistently delivering their best in every task, sharing their unique abilities and eccentricities, and upholding our core values: Curiosity, Dynamism, and Authenticity.
Responsibilities:
- Lead the design, development, and maintenance of a sophisticated data pipeline architecture.
- Compile complex and extensive datasets that suit both functional and non-functional business requirements precisely.
- Lead the identification, design, and execution of internal process improvements, including automating manual tasks, optimizing data delivery, and redesigning infrastructure for improved scalability.
- Oversee and coordinate the activities and deliverables of the Data Engineering team, providing mentorship and direction to junior team members.
- Conduct detailed reviews and proficiently manage source code using Git, ensuring high-quality codebase standards.
- Assist Data Engineers in building the necessary infrastructure for smooth data extraction, transformation, and loading from a diverse range of data sources such as Zendesk, Freshdesk, QuickBooks, Sprout, Kustomer, etc.
- Write comprehensive database documentation, including data standards, procedures, and definitions for the data dictionary (metadata), contributing to a well-structured data ecosystem.
- Administer access permissions and privileges across all managed databases, maintaining robust security practices.
- Work closely with stakeholders and fellow Data Engineers to solve complex data-related technical challenges and meet their developing data infrastructure needs, demonstrating strong cross-functional teamwork.
Requirements:
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- +5 years of experience in building and optimizing data pipelines, architectures, and datasets.
- Strong analytical skills related to working with unstructured datasets.
- Intermediate project management and organizational skills.
- +5 years of experience with data pipeline and workflow management tools, especially using Airflow and AWS tools.
- Experience with ETL (Extract-Transform-Load), data integration, manipulation, transformation, and cleaning with scripting languages such as Python, Java, etc.
- Experience with AWS cloud services: Lambda, SNS, RDS, Redshift, API Gateway, S3, VPC, etc.
- Experience with Google Cloud Platform.
- Intermediate knowledge of data transfer, backup, recovery, security, integrity, and SQL
- +5 years of experience with RESTful Services and APIs
- A general understanding of the Philippines Data Privacy Act
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, PHP, etc.
- +3 years of programming experience
- Working knowledge with version control tool like Github
- AWS Solutions Architect (Associate) Certification is a must.
- AWS Solutions Architect (Professional) Certification is a plus.
