- Effectively communicate complex data problems by tailoring the message to the audience and presenting it clearly and concisely.
- Balance multiple perspectives, disagree, and commit when necessary to move key company decisions and critical priorities forward.
- Have a profound comprehension of data quality, governance, and analytics.
- Ability to work independently in a dynamic environment and proactively approach problem-solving.
- Is committed to driving positive business outcomes through expert data handling and analysis.
- Be an example for fellow engineers by showcasing customer empathy, creativity, curiosity, and tenacity.
- Have strong analytical and problem-solving skills, with the ability to innovate and adapt to fast-paced environments.
- Design and build clear, understandable, simple, clean, and scalable solutions.
- Architect, strengthening, and expanding the core data products to scale our business, integrating data from multiple sources into a cohesive structure.
- Take full ownership of significant portions of our data products, including collaborating with stakeholders on the data model, designing large-scale data processing solutions, and ensuring the delivery of high-quality data on time.
- Work alongside Analytics Engineers, Data Scientists, and Software Engineers to develop intuitive data products for analysis, machine learning, and reporting.
- Manage data warehousing solutions, develop scalable data processing solutions, and ensure adherence to data governance policies.
- Design scalable and reliable data pipelines to integrate and analyze large volumes of data from diverse sources, supporting our business's growing needs.
- Collaborate across teams to define our data roadmap, working alongside data scientists, machine learning engineers, and product and business leaders to identify and prioritize key data initiatives.
- Building and maintaining frameworks to measure and monitor data quality and integrity, ensuring our data assets remain accurate and reliable.
- Architect, deploy, and optimize Databricks solutions on AWS, developing scalable data processing solutions, implementing CI/CD processes for these solutions, and leveraging infrastructure-as-code tooling to streamline data operations and enhance data solution deployments.
- Implement data solutions using cutting-edge technologies like Spark, Python, Databricks, and various AWS services (S3, Redshift, EMR, Athena, Glue).
- Mentor and coach fellow engineers on the team, fostering an environment of growth and continuous improvement.
- Identify and address gaps in team capabilities and processes to enhance team efficiency and success.
- Apply statistical analytical techniques to tackle complex data challenges, innovate with new technologies and methods to solve business problems, and work on diverse, geographically distributed project teams.
- Ideally has over 10 years of experience in data engineering, including at least 5 years of experience as a data architect and extensive expertise in designing and leading complex data warehousing, data modeling, and data transformation projects for both batch and streaming systems. Have successfully navigated the challenges of working with large-scale data systems.
- Deep understanding of data processing, comfortable working with multi-terabyte datasets, and skilled in high-scale data ingestion, transformation, and distributed processing, with strong Apache Spark (Scala or Python) capabilities.
- Hands-on experience with command programming languages such as Python, Scala, or Java, as well as data exploration using SQL
- Hands-on expertise in data technologies with proficiency in technologies such as Spark, Airflow, Databricks, AWS services (SQS, Kinesis, etc.), and Kafka. Understand the trade-offs of various architectural approaches and recommend solutions suited to our needs.
- Experience with the latest technologies and trends in Data and Cloud platforms.
- Database and analytics expertise, familiarity with a broad range of databases and analytics technologies (data warehousing, data lakes, ETL, relational databases), and ability to navigate the landscape to deliver effective data solutions.
- Leadership and mentorship demonstrate the ability to mentor engineers, fostering their growth and development, and you have successfully partnered with product and machine learning teams on strategic data initiatives.
- Commitment to quality, you take pride in delivering work that excels in data accuracy, performance, and reliability, setting a high standard for the team and the organization.
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Data Platform Architect - São Paulo, Brasil - Signifyd
Descrição
MUST APPLY IN ENGLISH
We are seeking a highly skilled and experienced Data Platform Architect to join our dynamic and growing data platform team. As a Data Platform Architect, you will play a crucial role in strengthening and expanding the core of our data products. Your responsibilities will include scaling our business, supporting data-driven decisions, and contributing to our overall data strategy. You will work alongside talented data platform engineers to envision how all the data elements from multiple sources should fit together and then execute that plan. The ideal candidate must:
Responsibilities:
Requirements for position :
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We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
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