Job
Description
What Youll Do Architect and scale modern data infrastructure: ingestion, transformation, warehousing, and access Define and drive enterprise data strategygovernance, quality, security, and lifecycle management Design scalable data platforms that support both operational insights and ML/AI applications Translate complex business requirements into robust, modular data systems Lead cross-functional teams of engineers, analysts, and developers on large-scale data initiatives Evaluate and implement best-in-class tools for orchestration, warehousing, and metadata management Establish technical standards and best practices for data engineering at scale Spearhead integration efforts to unify data across legacy and modern platforms What You Bring Experience in data engineering, architecture, or backend systems Strong grasp of system design, distributed data platforms, and scalable infrastructure Deep hands-on experience with cloud platforms (AWS, Azure, or GCP) and tools like Redshift, BigQuery, Snowflake, S3, Lambda Expertise in data modeling (OLTP/OLAP), ETL pipelines, and data warehousing Experience with big data ecosystems: Kafka, Spark, Hive, Presto Solid understanding of data governance, security, and compliance frameworks Proven track record of technical leadership and mentoring Strong collaboration and communication skills to align tech with business Bachelors or Masters in Computer Science, Data Engineering, or a related field Nice To Have (Your Edge) Experience with real-time data streaming and event-driven architectures Exposure to MLOps and model deployment pipelines Familiarity with data DevOps and Infra as Code (Terraform, CloudFormation, CI/CD pipelines) (ref:hirist.tech) Show more Show less
