Lead Data Engineer/Data Architect
hace 2 días
Manager-Recruitment & Client Engagement| Global (India, North America, and LATAM) | H1b Transfer | Green Card/Perm Filling. Position: Lead/Principal Data Engineer/Data Architect Client Domain: Banking Institution Work Structure Initial Phase: Mandatory 3 weeks on-site in Mexico City (Santa Fe) for essential client immersion and team onboarding. Ongoing: Following the initial phase, the role transitions to fully remote. Note on Expenses: The client will not cover travel, lodging, or living expenses for the initial 3-week on-site period. About the Opportunity We are seeking a highly skilled and experienced Data professional for a challenging and impactful role, which may be scoped as a Lead Data Engineer, Principal Data Engineer, or Data Architect, depending on experience and expertise. You will be instrumental in designing, building, and optimizing cutting-edge data platforms and pipelines for our major banking client. This is a chance to define the future of data architecture in a high-stakes, high-volume environment. Architecture & Design: Lead the design and implementation of modern data architectures (Data Lakes, Lakehouses, Data Hubs) on major cloud platforms. Pipeline Development: Develop robust, scalable, and high-performance data pipelines for ingestion, transformation, and consumption, utilizing both batch and streaming techniques. Technical Leadership: Drive best practices in data governance, data quality, security, and observability across all data products. Performance Optimization: Tune and debug complex Spark jobs and data flows to ensure optimal performance and cost efficiency. DevOps & Automation: Implement and maintain robust DevOps practices, including CI/CD pipelines for data infrastructure and application deployment. Preferred Qualifications Data Architecture & Cloud Cloud Environments: Deep, hands-on experience developing and deploying production data systems on major cloud platforms (AWS, GCP, Azure). Data Architecture: Proven track record building modern data architectures, including Data Lakes, Data Lakehouses, and Data Hubs. Data Governance & Observability: Strong background in defining and implementing data governance, modeling, and observability capabilities. Data Ingestion & Storage: Proficiency with data collection/ingestion tools (Kafka, AWS Glue). Expertise in working with modern storage formats (Iceberg, Parquet). Data Streaming: Experience developing data pipelines using streaming architectures and tools (Kafka, Flink). Data Modeling & Transformation: Expertise in data transformation and modeling using SQL-based frameworks and orchestration tools (dbt, AWS Glue, Airflow). Deep experience with advanced modeling concepts like Slowly Changing Dimensions (SCD) and schema evolution. Spark & Performance: Strong background in using Spark for large-scale data transformation, including streaming, advanced performance tuning, and debugging with Spark UI. Core Skills Programming: Advanced programming skills in Python, Java, Scala, or similar languages. SQL: Expert-level proficiency in SQL for complex data manipulation, query optimization, and performance analysis. DevOps: Demonstrated experience in DevOps practices, including code management (Git), CI/CD, and robust deployment strategies. Data Governance: Solid understanding of data governance principles, focusing on data quality, privacy, and security considerations relevant to the banking sector. If you are a visionary Data Architect or a highly skilled Lead/Principal Data Engineer looking to make a significant impact in the FinTech space, we encourage you to apply by sharing chandan.s@globalapplications.com #J-18808-Ljbffr
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Lead Data Engineer
hace 2 días
Mexico City Global Applications Solution A tiempo completoA leading technology firm seeks a skilled Lead Data Engineer/Data Architect in Mexico City. This role involves designing cutting-edge data architectures and optimizing data pipelines for a major banking client. Candidates should have advanced programming skills in Python and SQL, along with experience in cloud environments like AWS, GCP, and Azure. This...
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