Shared jobData Engineer
Pune · Mid Level
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MEDIUM
Tvarit is reviewing applications at a steady pace. Expect a standard response time as they evaluate the current pool.
First 72 hours
Window passed - posted 302d agoEarly applicants get seen before the pile builds.
Not a repost
The first time we've seen this listing - it hasn't been closed and reopened.
Skills required
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Job description
About TVARIT
Job Description
Key Responsibilities
- Build scalable real-time and batch processing workflows using Azure Databricks, PySpark, and Apache Spark.
- Perform data pre-processing, including cleaning, transformation, deduplication, normalization, encoding, and scaling to ensure high-quality input for downstream analytics.
- Design and maintain cloud-based data architectures, including data lakes, lakehouses, and warehouses, following Medallion Architecture.
- Deploy and optimize data solutions on Azure (preferred), AWS, or GCP, with a focus on performance, security, and scalability.
- Develop and optimize ETL/ELT pipelines for structured and unstructured data from IoT, MES, SCADA, LIMS, and ERP systems.
- Automate data workflows using CI/CD and DevOps best practices, ensuring security and compliance with industry standards.
- Monitor, troubleshoot, and enhance data pipelines for high availability and reliability.
- Utilize Docker and Kubernetes for scalable data processing.
- Collaborate with the automation team, data scientists, and engineers to provide clean, structured data for AI/ML models.
Desired Skills and Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
- Minimum 2 years of experience in data engineering, with a strong focus on cloud platforms such as Azure (preferred), AWS, or GCP.
- Proficiency in PySpark, Azure Databricks, Python, and Apache Spark.
- Expertise in relational databases (e.g., SQL Server, PostgreSQL), time-series databases (e.g., InfluxDB), and NoSQL databases (e.g., MongoDB, Cassandra).
- Experience in containerization (Docker, Kubernetes).
- Strong analytical and problem-solving skills with attention to detail.
- Good to have knowledge of MLOps, DevOps, and model lifecycle management.
- Excellent communication and collaboration skills, with a proven ability to work effectively as a team player.
- Comfortable working in a dynamic, fast-paced startup environment, adapting quickly to changing priorities and responsibilities.
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