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Lowe's

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4.2

based on 788 Reviews

Video summary

95 Lowe's Jobs

Data Engineer - ML_Pyspark

Lowes Services India Private limited

4.2

based on 788 Reviews

2-5 years

₹ 5 - 21.3L/yr (AmbitionBox estimate)

Bangalore / Bengaluru

1 vacancy

Data Engineer - ML_Pyspark

Lowe's

posted 4hr ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analytics Python Supply Chain Management SQL Business Analytics Product Management

+ 3 more

Job Description

The primary purpose of this role is to design, build, and maintain the data systems and pipelines that enable the organization to collect, store, process, and analyze large volumes of data. The main goal is to ensure that data is accessible, reliable, and structured in a way that facilitates easy use by data scientists, analysts, and other decision-makers. Along with Data Engineering Pipeline, the Data AI/ML Engineer will apply foundational ML knowledge to assist in optimizing model performance, developing necessary tools and frameworks, and efficiently managing computing and storage resources. This role will harness AI/ML platform capabilities and help accelerate the development of AI/ML-driven products.

Roles Responsibilities:

Working closely with the data science team to develop data models and pipelines for ML Forecasting, contributing to build, enhance, maintain and optimize state-of-the-art data/ML pipelines for ML predictive models.
Collaborating with Data Scientists to build the data preprocessing, feature engineering post processing jobs to ensure that the data used for training the models is of high quality ready.
AI/ML Models path to production - Responsible for deploying the models into production monitoring its performance to oversee its performance and bringing out improvements plan.
Developing transformation modules to aggregate, filter, and combine multiple datasets, creating key business-ready datasets and metrics for data visualization insights
Collaborating with Data Scientist to scale the model for data and SLA requirement.
Collaborating with the Business and Product teams to deliver analytics and reports.
Designs develops integrated business and enterprise application solutions in the data engineering and analytics domain, ensuring that the solutions are flexible, scalable, maintainable, and align with architectural standards.
Supports the implementation of security and compliance measures within the AI/ML development process, aligning with company policies and industry regulations.
Championing best practices and consistently working to enhance our production pipelines to improve reliability, scalability, and efficiency in terms of both time and memory.

Years of Experience:

2 - 5 years of experience in Data AI/ML engineering,

Required Minimum Qualifications :

Bachelors/masters degree in engineering, Computer Science, CIS, or related field (or equivalent work experience in a related field)
Minimum 2 years of experience in applications powered by AI/ML with large dataset
1 year of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC)

Skill Set Required :

Experience with Data engineering building Data/ML pipelines for AI/ML Models business analytics insights.

Hand-on experience (real-time) proficiency in building robust, reliable scalable data/ML pipelines for Analytics AI/ML systems, working with large sets of structured and unstructured data from disparate sources
ML Engineering in taking AI/ML models to production, performance/execution optimization.
SQL
Python
Spark, PySpark
Big Data systems - Hadoop Ecosystem (HDFS, Hive, MapReduce) or Cloud
Analytics database like Druid, Data visualization/exploration tools like Superset.
CI\CD
GIT

Secondary Skills (desired) :

Apache Airflow, Apache Oozie, Nifi
GCP cloud experience, Big Query
Trino/Presto
ML Flow
Experience working on Data Quality/Integrity theme, Tools like Great Expectations.
Domain experience on retail forecasting or any other business forecast predictions/time series forecasting