Data Engineer

Data Engineer

This role will be part of Global Technology & Information Security & Privacy under Performance Metrics and
Analytics function with primarily responsibility of developing and implementing in-house-driven data analytics and security automation program that are aimed to strengthen the overall Information Security & Technology governance through automated discovery of measurable security risks, automated orchestration of risk reduction exercise and visualization of reduction of risks / risk exposures.

Cloud Platform Data Services, Data analytics and Machine Learning.

RESPONSIBILITIES
- Research and implement best practices to build a modern data architecture with optimal data ingestion pipelines, data transformation and machine learning capabilities with Google Cloud

Platform data technologies. This includes maintaining/optimizing existing data pipeline platform usingPython programming on AKS and Azure Data stack.
- Analyse, assemble, and transform large, complex raw data sets to be ready for data analytics to support analytics initiatives in Azure & GCP. Develop analytical tools and programs.
- Evaluate business needs and objectives, identify potential Machine Learning use cases and translating data requirements into business improvement through data analytics.
- Oversee the entire lifecycle of data engineering & analytics (research, design, experimentation, development, deployment, monitoring, and maintenance).
- Subject Matter Expert for data technologies in GCP & Azure, Data Analytics & AI.
- Good understanding of migration and modernization strategies and approaches to plan for migration, build or expand data analytics, data pipelines and ML domains.

**REQUIREMENTS**:
Technical Skills:

- Hands on experience with Google Data Services and products like BigQuery, DataFlow, Dataproc,

Kafka, Looker, Data Fusion etc.
- Advance proficiency in Programming languages in Python, NumPy, pandas, scikit-learn, TensorFlow,

Spark (Python/Scala), and working knowledge of relational database in SQL and NoSQL is desired.
- Technical proficiency in Azure required in Microsoft Azure Data Services - Azure Synapse, Azure Data

Factory, Azure Data Lake, Azure Databricks, Azure Machine Learning. - across scenarios like Data
Migration, Data Modernization, Modern Data Warehouse, Azure ML, etc.
- Understanding of data structures, data modeling techniques and software architecture
- Hands-on working experience in data mining, data wrangling, and experience with handling JSON,

CSV, pickle, parquet files etc.
- Hands-on experience with developing large-scale supervised and unsupervised machine learning models

Leadership Skills:

- Excellent in communicating clear, concise and understandable messages verbally and through communication packs to various stakeholders.
- Excellent in articulating technical algorithms and mechanisms to senior management and group leaderships.

Problem Solving:

- Able to define clear problem statements and articulate clearly and efficiently to the targeted audience.
- A good team player who is willing to contribute at all levels to ensure team success.
- Proactive in suggesting improvements.
- Ensure long term operational efficiency of all suggested solutions and implementations.

EXPERIENCE / QUALIFICATIONS
- Experience in creating data pipelines for on-cloud ETL processing; copy activity, custom script development etc.
- Highly self-driven, demonstrate critical thinking, team player & fast learner.
- Good analytical skills with the ability to work independently and effectively as a team.
- Solid background in data engineering and machine learning.
- Past experiences in: o Open source DevOps tools and software as a service solution. o Software Development and implementation of AI and machine learning algorithms. o Good communications skills in both written and verbal English; and o An adventurous spirit and willingness to learn and experiment with new ideas and new domains.

**Job Types**: Full-time, Permanent

**Salary**: $7,000.00 - $8,000.00 per month

**Benefits**:

- Work from home

Schedule:

- Monday to Friday

Supplemental Pay:

- Performance bonus

**Education**:

- Bachelor's or equivalent (preferred)