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eligarf Technologies
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Data Engineer
eligarf Technologies
posted 16d ago
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Flexible timing
Key skills for the job
Job Description
- Develop & Maintain Data Pipelines: Design and build high-performance ETL/ELT pipelines for AI/ML workloads.
- AI Data Infrastructure: Architect and optimize data lakes, data warehouses, and vector databases (FAISS, Pinecone, Weaviate) to support AI-driven analytics.
- Big Data Processing: Handle large-scale structured and unstructured data using Apache Spark, Kafka, AWS Glue.
- AI Model Integration: Ensure efficient data ingestion and transformation for AI model training, including text-to-video, speech-to-text, and generative AI.
- Cloud & Infrastructure: Deploy and manage data pipelines on AWS (Lambda, S3, Redshift, DynamoDB, Bedrock, SageMaker). Experience with GCP/Azure is a plus.
- Data Governance & Security: Implement data quality checks, access control, and compliance using AWS IAM, AWS Lake Formation, and AWS Glue Data Catalog.
- Automation & Performance Tuning: Optimize data workflows, implement CI/CD pipelines, and ensure high availability.
- Collaboration: Work closely with AI/ML engineers, software developers, and DevOps teams to integrate AI-driven data solutions into production
Requirements- 8+ years of experience in Data Engineering, with a strong focus on AI-driven data solutions.
- Strong expertise in Python for data processing, automation, and AI/ML integration.
- Hands-on experience with AWS services (Lambda, S3, Redshift, DynamoDB, API Gateway, SageMaker, Bedrock).
- Experience with big data technologies like Apache Spark, Kafka, and AWS Glue.
- Proficiency in ETL/ELT processes and data warehousing solutions (AWS Redshift, Snowflake).
- Deep knowledge of vector databases (FAISS, Pinecone, Weaviate) for AI-powered search and retrieval.
- Experience in real-time AI data processing and event-driven architectures (AWS Kinesis, SNS, SQS).
- Strong database expertise in SQL (PostgreSQL, MySQL) and NoSQL (DynamoDB, MongoDB).
- Experience implementing CI/CD pipelines for data workflows using Terraform, Docker, and GitHub Actions.
- Ability to work in a UK time zone.
Preferred Qualifications:
- Experience in AI-powered media processing (text-to-video, speech-to-text, generative AI for media).
- Knowledge of MLOps, AI model deployment, and automated AI data pipelines.
- Experience with real-time data streaming frameworks (Flink, Apache Beam).
- Familiarity with AWS services for AI acceleration (Inferentia, Neuron SDK, SageMaker Pipelines).
- Experience in AI-powered media processing (text-to-video, speech-to-text, generative AI for media).
- 8+ years of experience in Data Engineering, with a strong focus on AI-driven data solutions.
Employment Type: Full Time, Permanent
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What people at eligarf Technologies are saying
Rating based on 8 Data Engineer
reviews
Anonymous · Data Science & Analytics
- Work from home - Salary on time - Team members are cooperative
- Not a place to learn and grow in career. - Management sucks - Exit policy is worst
- Salary - Poor
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eligarf Technologies Benefits
Work From Home Health Insurance Job Training Team Outings Rewards and Recognition 
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