Specialist - Data Engineering

Role description

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 Candidate will work with cuttingedge 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 ETLELT processes and a passion for building scalable and reliable data solutions

Key Responsibilities

• Design develop and maintain scalable and efficient data pipelines using Apache SparkJava Spark pySpark and Apache Flink for realtime 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 costefficiency


• 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

• Bachelors or Masters 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 data pipelines architectures and data sets


• Strong proficiency in programming languages such as Python with extensive pySpark experience Java or Scala


• Expertise in Apache Spark for data processing including Spark SQL DataFrames and RDDs


• Handson experience with Apache Hadoop ecosystem components particularly HDFS


• Experience with realtime 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 ETLELT processes data warehousing concepts and data modeling techniques


• Good to have experience with cloud platforms eg AWS Azure GCP and their data services


• Excellent problemsolving analytical and communication skills

Other details

Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):

Benefits and Perks:

• Comprehensive Medical Plan Covering Medical, Dental, Vision


• Short Term and Long-Term Disability Coverage


• 401(k) Plan with Company match


• Life Insurance


• Vacation Time, Sick Leave, Paid Holidays


• Paid Paternity and Maternity Leave

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and 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 like an annual performance-based bonus, sales incentive pay and other forms of bonus or 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 that is 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.