Specialist - Architecture

Mandatory Skills

GCP BigQuery Kafka Dataflow Apache Spark Data Spark Vertex AI Cloud Storage Adobe Analytics Python Java Nodejs Experience Senior Data Engineer Platform ML Analytics 79 years in data engineering or ML data engineering Data Engineer II ML Training MultiSource Integration 57 years in data or ML data engineering Job Description

Required Qualifications 79 years of handson data engineering or ML data engineering experience in a production GCP environment Strong proficiency in Python Java or Nodejs for pipeline development feature engineering scripts and automation Strong handson experience with BigQuery partitioning clustering cost management complex SQL MLoptimized table design Proficiency with Apache Kafka for realtime streaming ingestion Experience with Dataflow Apache Beam for both streaming and batch pipelines Proficiency with Apache Spark PySpark or Scala DataSpark experience a strong plus Solid familiarity with GCP ecosystem Cloud Storage PubSub Dataproc Cloud ComposerAirflow Experience building ML training pipelines and Feature Stores GCP Feature Store preferred understanding of the ML lifecycle including feature engineering data versioning and traineval splits Experience with Vertex AI Pipelines or similar MLOps tooling Demonstrated experience designing disaster recovery zones and failover strategies for cloud data platforms crossregion replication RTORPO definition and DR testing Experience with data archival design BigQuery table lifecycle management Cloud Storage tiered storage policies and longterm retention for regulated datasets Handson experience handling PHI under HIPAA fieldlevel encryption and masking deidentification techniques audit logging access control policies and HIPAA Security Rule compliance for data at rest and in transit Strong SQL and data modeling skills experience with layered data lake or lakehouse architecture Nice to Have Experience integrating Adobe Analytics data streams or Adobe Experience Platform Familiarity with Looker or Vertex AI as downstream consumers Knowledge of ClickThru file formats and external table patterns in BigQuery Experience with GCP CMEK CustomerManaged Encryption Keys for PHI dataset protection Familiarity with HIPAA BAA requirements in cloud vendor agreements CVS Digital AI Insight NBA Engine Data Layer Job Descriptions For Recruitment Use Only Not for Distribution Page 4 Familiarity with NIST or HITRUST frameworks as applied to ML data pipelines Background in healthcare data Rx clinical or benefits domain

Mandatory Skills : Apache Spark, GCP Vertex AI, Machine Learning Algorithms, Vertex AI

Actual compensation within the range will be dependent upon the individual's skills, experience, performance and internal equity.

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.