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Data Engineer
1 month ago
We are seeking a detail-oriented Machine Learning Data Engineer to join our team. As a Client Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines that ingest, transform, and load data from various sources into our cloud-based systems. You will work closely with machine learning teams to ensure that data is accurate, enriched, reliable, and readily available for analytics and model training.
Responsibilities:
Design and Build Data Pipelines: Create efficient, reliable, streamable, and scalable data pipelines using industry-standard tools and techniques, such as TorchData, WebDataset, Apache Parquet., Python, and SQL.
Data Ingestion: Develop strategies for ingesting data from data providers, ensuring data quality and consistency.
Data Pre-processing: Implement parallel pre-processing to clean, transform, de-duplicate, combine and normalize data.
Data Curation and Enrichment: Curate, augment, and enrich existing datasets to improve data quality and provide valuable insights to stakeholders.
Synthetic Data Generation: Collaborate with synthetic data teams to generate data and incorporate into existing pipelines.
Collaboration with Client Teams: Work closely with Client scientists, engineers, and product teams to understand data requirements, and collaborate on data delivery.
Monitoring, Maintenance & Updating: Monitor data pipelines for performance, errors, and bottlenecks, and implement regular maintenance and updates. Stay updated with the latest trends and incorporate best practices into data pipelines.
Technical Documentation: Document data pipelines, settings, and procedures for easy maintenance and knowledge sharing.
Minimum Qualifications:
Bachelor’s degree in Computer Science, Information Technology, or a related field.
At least 3 years of experience as a Software Engineer or Data Engineer.
Strong software engineering skills, proficiency in Python
Experience with data processing tools and formats such as Apache Parquet, WebDataset, TorchData, Pandas, Shell Scripting, Protobuf, TFRecord
Knowledge of data warehouse architectures and cloud-based systems (e.g., AWS S3).
Strong problem-solving and analytical skills.
Excellent communication and collaboration skills.
Preferred Qualifications:
Master’s degree in Data Science or a related field.
Experience with data curation and enrichment techniques, particularly for large scale text, image and video data
Familiarity with natural language processing (NLP), machine learning (Client) concepts and frameworks (PyTorch)
“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”
