Specialist - Data Engineering

Job Title: Specialist data engineering (Need Iceberg and Flink) Work Location : Tampa, Florida Job Description About the Role: We are seeking a highly skilled and experienced Data Engineer to join our growing data team. This role will be instrumental in designing, building, optimizing, and maintaining our robust data infrastructure and pipelines. The candidate will work with cutting‑edge big data technologies to ingest, process, store, and transform large datasets, enabling advanced analytics and machine learning initiatives across the organization. The ideal candidate will have a deep understanding of data warehousing, ETL/ELT processes, and a passion for building scalable and reliable data solutions. Key Responsibilities Design, develop, and maintain scalable and efficient data pipelines using Apache Spark, Java, PySpark, and Apache Flink for real‑time and batch processing of large datasets. Implement and manage data storage solutions leveraging Hadoop Distributed File System (HDFS) and data lake table formats like Apache Iceberg. Build and optimize data models and schema definitions for various data sources and targets, ensuring data quality, consistency, and accessibility. Work with stakeholders to understand data requirements, translate them into technical specifications, and deliver robust data solutions. Monitor, troubleshoot, and optimize existing data pipelines and infrastructure for performance, reliability, and cost‑efficiency. Develop and implement data governance, security, and compliance best practices within the data ecosystem. Collaborate with data scientists, analysts, and other engineering teams to support their data needs and integrate new data sources. Evaluate and recommend new technologies and methodologies to enhance our data platform capabilities. Ensure proper documentation of data architectures, pipelines, and processes. Required Skills & Experience Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field. Proven experience as a Data Engineer or in a similar role building and optimizing big data pipelines, architectures, and datasets. Strong proficiency in programming languages such as Python (extensive PySpark experience) and Java or Scala. Expertise in Apache Spark for data processing, including Spark SQL, DataFrames, and RDDs. Hands‑on experience with Apache Hadoop ecosystem components, particularly HDFS. Experience with real‑time stream processing using Apache Flink. Familiarity with data lake table formats, specifically Apache Iceberg, for managing large evolving datasets. Experience with relational SQL and NoSQL databases. Solid understanding of ETL/ELT processes, data warehousing concepts, and data modeling techniques. Good to have experience with cloud platforms such as AWS, Azure, or GCP and their data services. Excellent problem‑solving, analytical, and communication skills. Benefits and Perks Comprehensive medical plan covering medical, dental, and vision. Short‑term and long‑term disability coverage. 401(k) plan with company match. Life insurance. Paid paternity and maternity leave. Vacation time, sick leave, and paid holidays. The range displayed on each job posting reflects the minimum and maximum salary target for the position across all U.S. locations. Within the range, individual pay is determined by work location, job level, and additional factors including job‑related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation, such as an annual performance‑based bonus, sales incentive pay, and other variable compensation. Disclaimer : The compensation and benefits information provided herein is accurate as of the date of this posting. LTIMindtree is an equal‑opportunity employer committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family‑care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law. #J-18808-Ljbffr