Lead Data Engineer/Data Architect

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 #J-18808-Ljbffr