Job Title: Data/ ML-Ops Engineers

Location: Andheri

Company Overview:

Spinnaker Analytics is a leading predictive analytics and artificial intelligence company headquartered in Boston, USA, with a global presence. We specialize in building predictive models and algorithms to solve critical business challenges across various industries. Leveraging predictive analytics, AI, machine learning, and deep domain expertise, we develop innovative analytic products and decision-making tools. For more information, visit ww.spinnakeranalytics.com.

Profile Overview

We're seeking talented Data/ML-Ops Engineers to join our team. In this role, you'll play a key part in the data lifecycle, transforming raw data into valuable insights for data analysis and machine learning projects. You'll design and build data pipelines, ensuring data quality and collaborating closely with data scientists and business users.

Responsibilities

• Analyze raw data, identify and address quality issues (completeness, duplicates, outliers) using SQL, Python libraries (Pandas, NumPy), and other data manipulation tools.

• Design, develop, and maintain data pipelines for data extraction, transformation, and loading (ETL)

• Perform data integrity checks and automate manual data processes for efficiency.

• Utilize statistical analysis and data visualization methods to explore data and prepare it for modelling.

• Deliver data sets in formats suitable for machine learning algorithms used by data scientists.

• Collaborate with data scientists and business users to understand data structures, variables, and systems.

• Troubleshoot data-related technical issues with data analysts and business teams.

• Define user access and ensure data distribution to the right users in the appropriate format and timeframe.

Technical Skills & Requirements

• Essential:

✓ 3+ years of experience in data manipulation and wrangling for analytics.

✓ Proficiency in SQL (including stored procedures) or NoSQL databases.

✓ Strong understanding of data structures and design principles.

✓ Experience with Python libraries for data manipulation (Pandas, NumPy, etc.)

✓ Experience with Azure cloud tools like Azure Data Factory, Synapse, etc. and the medallion lake house architecture.

✓ Experience in containerizing solutions for CI/CD (Continuous Integration/Continuous Deployment) flows using Azure Containers, Kubernetes, Docker etc.

• Desirable:

✓ Certification in MS SQL or a similar data warehousing or data management solution (SSIS/SSRS/SSAS).

✓ Familiarity with cloud platforms (AWS, GCP, Azure) a plus.

✓ Experience with data warehousing concepts and tools.

✓ Knowledge of data version control systems (e.g., Git).

Soft Skills

✓ Excellent collaboration skills to work effectively with data scientists, analysts, and business users.

✓ Positive and proactive approach to problem-solving.

✓ Strong communication skills to explain technical concepts to non-technical audiences.