Data Engineering Manager at Network Science · Mumbai, Navi Mumbai · 5 - 8 years · ₹20L - ₹25L / yr · Bootstrapped · Posted 15 Sep 2022
- Collaborate with the business teams to understand the data environment in the organization; develop and lead the Data Scientists team to test and scale new algorithms through pilots and subsequent scaling up of the solutions
- Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service
- Act as the single point source for all data related queries; strong understanding of internal and external data sources; provide inputs in deciding data-schemas
- Design, develop and maintain the framework for the analytics solutions pipeline
- Provide inputs to the organization’s initiatives on data quality and help implement frameworks and tools for the various related initiatives
- Work in cross-functional teams of software/machine learning engineers, data scientists, product managers, and others to build the AI ecosystem
- Collaborate with the external organizations including vendors, where required, in respect of all data-related queries as well as implementation initiatives

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We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.
Hiring for Data Scientist / Senior Data Scientist
Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.






