Job
Description
Job Description: We are seeking a highly experienced Data Architect with 15-20 years of experience to lead the design and implementation of data solutions at scale. The ideal candidate will have deep expertise in cloud technologies, particularly GCP, along with a broad skill set in SQL, BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, DLP, Dataproc, Cloud Composer, Python, ETL, and big data technologies like MapR/Hadoop, Hive, Spark, and Scala. Key Responsibilities: Lead the design and implementation of complex data architectures across cloud platforms, ensuring scalability, performance, and cost-efficiency. Architect data solutions using Google Cloud Platform (GCP) services such as BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, Dataproc, Cloud Composer, and DLP. Design and optimize ETL - Abinitio processes and data pipelines using Python and related technologies, ensuring seamless data integration across multiple systems. Work with big data technologies including Hadoop (MapR), Hive, Spark, and Scala to build and manage large-scale, distributed data systems. Oversee the end-to-end data flow from ingestion to processing, transformation, and storage, ensuring high availability and disaster recovery. Lead and mentor a team of engineers, guiding them in adopting best practices in data architecture, security, and governance. Define and enforce data governance, security, and compliance standards to ensure data privacy and integrity. Collaborate with cross-functional teams to understand business requirements and translate them into data architecture and technical solutions. Design and implement data lake, data warehouse, and analytics solutions to support business intelligence and advanced analytics. Lead the integration of cloud-native tools and services for real-time and batch processing, using Pub/Sub, Dataproc, and Cloud Composer. Conduct performance tuning and optimization for SQL, BigQuery, and big data technologies to ensure efficient query execution and resource usage. Provide strategic direction on new data technologies, trends, and best practices to ensure the organization remains competitive and innovative. Required Skills: 15-20 years of experience in data architecture, data engineering, or related roles, with a focus on cloud solutions. Extensive experience with Google Cloud Platform (GCP) services, particularly BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, Dataproc, Cloud Composer, and DLP. Strong Experience in ETL - Abinitio. Proficient in SQL and experience with cloud-native data storage and processing technologies (BigQuery, Hive, Hadoop, Spark). Expertise in Python for ETL pipeline development and data manipulation. Solid understanding of big data technologies such as MapR, Hadoop, Hive, Spark, and Scala. Experience in designing and implementing scalable, high-performance data architectures and data lakes/warehouses. Deep understanding of data governance, security, privacy (DLP), and compliance standards. Proven experience in leading teams and delivering large-scale data solutions in cloud environments. Excellent problem-solving, communication, and leadership skills. Ability to work with senior business and technical leaders to align data solutions with organizational goals. Preferred Skills: Experience with other cloud platforms (AWS, Azure). Knowledge of machine learning and AI data pipelines. Familiarity with containerized environments and orchestration tools (e.g., Kubernetes). Experience with advanced analytics or data science initiatives.
