Akhila Labs, LLC
Website:
akhilalabs.com
Job details:
Data Engineer
Company Description
Akhila Labs is a global Product Engineering Services company specializing in transforming complex silicon designs into market-ready products. With expertise spanning embedded systems, hardware design, and cloud-native applications, the company provides end-to-end engineering solutions that bridge hardware and software.
Akhila Labs serves industries such as automotive, healthcare, industrial automation, and consumer electronics, focusing on scalability, security, and efficiency. From custom board design to deploying scalable IoT architectures, Akhila Labs empowers businesses to accelerate time-to-market and deliver next-generation connected devices.
Role Description
This is a full-time on-site role based in Ahmedabad for a skilled Data Engineer. The role involves building cloud-native data pipelines on AWS, with a strong focus on unstructured data (text & audio) for AI and analytics applications.
Key Responsibilities
- Build scalable batch and near real-time data pipelines
- Process and manage unstructured data including logs, transcripts, recordings, and audio streams
- Develop AI-ready datasets for downstream analytics and ML workflows
- Implement data quality checks, monitoring, and cost optimization strategies
- Build and maintain ETL/ELT workflows and orchestration pipelines
- Work with Kubernetes-based deployments and collaborate closely with AI and backend engineering teams
- Develop and maintain web scraping/crawling pipelines for structured and unstructured data extraction
Required Skills
- Strong hands-on expertise in Python
- Advanced SQL and strong database fundamentals
- Experience building ETL/ELT data pipelines
- Hands-on experience with web scraping/crawling tools such as Scrapy, BeautifulSoup, Selenium, or Playwright
- AWS services: S3, Glue, Athena, Lambda, IAM, CloudWatch
- Workflow orchestration tools such as Airflow, Prefect, or Dagster
- Experience handling text and audio datasets
- Basic understanding of AI/ML concepts
- Knowledge of embeddings and vector databases
- Docker and Kubernetes fundamentals
Preferred Qualifications
- Experience working with AI/LLM data pipelines
- Familiarity with scalable cloud-native architectures
- Understanding of monitoring, logging, and distributed systems
- Ability to work in a fast-paced product engineering environment
Click on Apply to know more.