Data Architect

Looking for a data professional with expertise in data engineering, programming and architect to build systems that collect, manage, and convert raw data into usable information for business requirements. As a Data Engineer architect, you’ll play a crucial role in ensuring data reliability, quality, and efficiency within the organization. Responsibilities s:Analyze and organize raw data: Work with various data sources, document parsing, extracting relevant information and structuring it for further processin g.Build data systems and pipelines: Construct robust data pipelines that facilitate data flow from source to Targe t.Evaluate business needs and objectives: Understand the company's requirements and align data systems accordingl y.Interpret trends and patterns: Use your analytical skills to identify data pattern s.Conduct complex data analysis and report on results: Dive deep into data to extract meaningful informatio n.Prepare data for prescriptive and predictive modeling: Ensure data is ready for machine learning and statistical analysi s.Build algorithms and prototypes: Develop and test data processing algorithm s.Combine raw information from different sources: Integrate data from various system s.Explore ways to enhance data quality and reliability: Continuously improve data processe s.Identify opportunities for data acquisition: Stay informed about new data source s.Develop analytical tools and programs: Create tools to facilitate data analysi s.Collaborate with data scientists and architects: Work closely with other data professionals to achieve common goal s.Implement data access controls, data encryption, and data masking techniqu esFamiliarity with data visualization tools and techniques for presenting da dataCreate and maintain dashboards and reports for stakeholder Mandatory Skills ls:15+ years in Data Engineering / Data Architect ureGood knowledge of programming languages (e.g., Python, Java, Spark, et c).Design, develop, and maintain data pipelin es.Exposure to process automati on.Experience working with REST APIs and services, messaging and event technologi es.Experience working with large and complex data se ts.Hands-on experience with SQL/No-SQL database (RDS, Redshift, DynamoDB, synapse, big query, mongo, et c.)Batch/stream data processing experie nceMonitor, troubleshoot, and optimize the performance of data infrastructure to ensure scalability, reliability, and cost efficien cy.Stay up to date with cloud services and best practices in data engineering to continuously improve our data ecosyst em.Good exposure on at least two public cloud platforms (Azure/AWS/G CP)Experience with Graph database (e.g. Neptune, RDF4j, et c.)Experience with Vector database (e.g. Pinecone, FAISS, et c.)Hands-on experience with ETL/ELT tools (Informatica, Talend, dbt, et c.)Expertise in cloud platforms: AWS / Azure / GCPExperience with big data technologies: Spark, Hadoop, Ka fkaStrong knowledge of data warehousing (Snowflake, Redshift, BigQue ry)Experience in building real-time and batch data pipeli nesStrong understanding of data governance and security framewo rksExperience with CI/CD, DevOps practices for data pipeli nesProven leadership and stakeholder management ski Good-to-Have Skills ls:knowledge or work experience in insurance, mortgage, banking domai ns.Proficiency in building stream processing systems using kinesis, Kafka, e tc.Familiarity with Docker, Kubernetes, CI/CD and cloud services (AWS, Azure, GC P).Technical expertise with segmentation techniqu #J-18808-Ljbffr