About Straive: Straive is a market leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains. Data Analytics & Al Solutions, Data Al Powered Operations and Education & Learning form the core pillars of the company’s long-term vision. The company is a specialized solutions provider to business information providers in finance, insurance, legal, real estate, life sciences and logistics. Straive continues to be the leading content services provider to research and education publishers. Data Analytics & Al Services: Our Data Solutions business has become critical to our client’s success. We use technology and Al with human experts-in loop to create data assets that our clients use to power their data products and their end customers & workflows. As our clients expect us to become their future-fit Analytics and Al partner, they look to us for help in building data analytics and Al enterprise capabilities for them. With a client-base scoping 30 countries worldwide, Straive’s multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore. About the Role: Looking for a professional leading the design, build and evolution of the inhouse data platforms. You lead the construction of datasets requested by various stakeholders, the build and maintenance of the resulting data pipelines. You closely work in collaboration with our data analysts, data scientist and business application development teams in delivering data solutions. Our hybrid work model is designed to give you the best of both worlds—flexibility and face-to-face collaboration. Employees are required to be present in the office on Mondays, Wednesdays and Fridays each week. This means you’ll be in the office at least three days a week, with the option to work remotely on the other days, based on manager approval and business needs. This approach helps us stay connected as a team while giving you the flexibility to work in a way that suits you. Required Qualifications: 10+ years of progressive experience in Data Engineering, with a minimum of 3–5 years in a data architecture or lead role. Deep expertise in modern data platforms such as Snowflake, Databricks, AWS/GCP/Azure, and orchestration tools like Airflow or Dagster. Strong command over Python, SQL, Spark, and data modeling frameworks. Experience in leading cross-functional teams including Data Scientists. Strong understanding of data governance, quality, and security frameworks. Preferred Skills: Familiarity with MLOps, model lifecycle management, and scalable ML deployment. Experience with Terraform, Kafka, Flink, dbt, or similar tools. Exposure to regulated data environments (Private equity, banking) is a plus. Strong communication and stakeholder management skills.
Job Title
Data Architect