Data Engineering Lead, Brazil
2 meses atrás
Locations:
São Paulo | Rio de Janeiro
Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.
We Are BCG XWe’re a diverse team of more than 3,000 tech experts united by a drive to make a difference. Working across industries and disciplines, we combine our experience and expertise to tackle the biggest challenges faced by society today. We go beyond what was once thought possible, creating new and innovative solutions to the world’s most complex problems. Leveraging BCG’s global network and partnerships with leading organizations, BCG X provides a stable ecosystem for talent to build game-changing businesses, products, and services from the ground up, all while growing their career. Together, we strive to create solutions that will positively impact the lives of millions.
What You'll DoJoin the BCG X Delivery team and immerse yourself in cutting-edge projects alongside our consulting units. Your role will be pivotal in employing data engineering methodologies to enhance the capabilities of both BCG Consulting and BCG X teams, across various domains. You'll be the go-to expert for data engineering, offering accelerated execution support to bring visions to life. Your collaboration will be key in understanding project requirements, leading the design, development, delivery, and support of solutions tailored to client needs. Expect to dive deep into tools and processes, ensuring the delivery of high-quality and efficient technology solutions. Whether it's short-term prototypes or long-term enterprise-grade developments, your contribution will significantly impact our project outcomes and organizational goals.
What You'll BringTechnical Skills - Knowledge and Experience with:
- Unix-based command line & development tools
- Version control (e.g. Git)
- Python Charting libraries (e.g. HighCharts, D3.js, Recharts, Plotly, Altair)
- Cloud computing platforms (e.g. AWS, Azure, Google Cloud, etc.)
- Containerization (Docker, Kubernetes, etc.)
- Relational databases (e.g. PostgreSQL, MariaDB, MySQL, etc.)
- NoSQL databases (e.g. MongoDB, Neo4j, Redis, etc)
- Spark or other distributed big data systems (e.g. Hadoop, Pig, Hive, etc.)
- Stream-processing frameworks (e.g. Kafka)
- Data pipeline orchestration tools (e.g. Airflow, Prefect, Dagster, etc.)
Job Requirements:
Bachelor's / Master's in Computer Science, a related field, or equivalent work experience
Fluency in Portuguese and English
Experience in Data Engineering across various industries, demonstrating a track record of delivering analytics solutions in commercial environments
Core attributes:
Harness Big Data tools and frameworks to fulfill specific requirements. Implement ETL processes across diverse architectures, ensuring optimal performance and advising on infrastructure enhancements. Collaborate with case and proposal teams to define analytics outcomes, select methodologies, and deliver unique insights. Lead analytics modules, establishing trust through expertise in analytics and effective communication of findings. Integrate learnings into new best practices, manage content confidentiality, and maintain stakeholder relationships for project security. Guide junior team members, contribute to intellectual property, and conduct technical training. Exhibit strong communication skills, both written and verbal, for clear message delivery. Utilize analytical skills throughout the analytics lifecycle, providing advice and expanding knowledge in advanced analytics.
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