Databricks Data Engineer

1 week ago

Noida, Uttar Pradesh, India Jellyfish Technologies Full time ₹ 15,00,000 - ₹ 28,00,000 per year

Role: Data Engineer Experience : 4-5 years

Location: Remote

About Us:

Jellyfish Technologies is a leader in leveraging cutting-edge data platforms to deliver innovative solutions. We're a company dedicated to creating scalable and efficient data ecosystems. We are seeking an experienced Databricks Architect to design and implement robust data solutions.

Position Summary:

We are looking for a Data Engineer with 4-5 years of professional experience. The ideal candidate will have a strong foundation in data engineering principles, with hands-on experience in building, maintaining, and optimizing data pipelines. Additionally, you will be skilled in applying statistical and machine learning techniques to solve complex business problems. You will work on various projects, from designing data architectures to developing predictive models, all in a collaborative and fully remote environment.

Key Responsibilities:

Data Engineering:

Design, develop, and maintain scalable and efficient data pipelines using ETL/ELT processes.

Build and optimize data models to support data-driven decision-making and analytics.

Manage and process large datasets from various sources, ensuring data quality and reliability.

Work with cloud-based data platforms such as Databricks, AWS, Azure, or GCP.

Troubleshoot and resolve data-related issues to ensure system stability and performance

Technical Skills:

Proficiency in programming languages like Python or Scala. o Strong expertise in SQL and working with relational databases.

Hands-on experience with big data technologies such as Apache Spark (Databricks is mandatory).

Experience with cloud platforms (AWS, Azure, or GCP). o Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib).

Solid understanding of machine learning models and statistical analysis.

Preferred Qualifications:
 Experience with MLOps frameworks like MLflow.  Knowledge of data warehousing solutions like Snowflake or Redshift.  Background in developing and deploying production-level machine learning models.

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