IN_Senior Associate_Google Cloud Certified_Data and Analytics_Advisory_Bangalore

You will be accountable for building & managing the data pipelines required to support Data loads and downstream reporting requirements.

You will help establish and validate the data sourcing requirements, build pipelines to curate data sets required and support the creation of output interfaces required for downstream consumption requirements, including reporting, model monitoring.

You will undertake these activities in a cross functional squad supported by SMEs, Business Analysts, Data Analysts & Engineers and more.

You will be collaborating to support the achievement of project or business outcomes such as process mapping and change transition as well as the technical implementation of the data processes.

You will ensure delivery of best practice end-to-end data engineering respecting best practices, policies and standards.

Aligned with the broader move to a Data Mesh and Data Product architecture on cloud platforms, you will help establish the starting point for other Data Portfolio teams to move to our next state architecture

Responsibilities:

• Design data structures and processes for data ingestion, integration and analytics layers on a variety of AWS (LAMBDA) & Google Cloud Platform (GCP) technologies (e.g. Cloud Run, CloudSQL, Google Cloud Storage, BigQuery, Vertex AI) and tooling such as DBT, PYTHON language working together to support the program workflow.

• Working in a cross skilled squad with people both from business and technology to build end to end capabilities and support project deliverable outcomes.

• Contribute to design patterns for on-premise and cloud.

• Optimise data flows by building robust, fault-tolerant data pipeline that cleans, transforms, and aggregates unorganized and messy data into databases or data sources.

• Implement automated controls to support data quality and process quality verification, auditability and reconciliation.

Knowledge, skills and experiences

• A strong background in data processing and software engineering and can build high quality, scalable data products

• Strong Software Engineering experience with proficiency in at least one high-level programming language (Python, Java, Scala)

• Experience and proficiency in Amazon & Google Cloud Platform technologies

• Strong ability to translate data insights into practical business recommendation

• Desirable to have good Commercial domain knowledge of Banking Systems

• Data Engineering Languages - Solving complex problems using programming techniques, drives consistency across teams, and Leading code quality improvements with large-scale changes.

• Data Flow Engineering - Designing and leading complex data flow projects, making informed choices about pipeline architectures and ensuring optimal performance.

• Data Quality Assurance - Leading the design and implementation of complex data flow solutions, making informed decisions on technical choices and ensuring optimal performance.

• Data Modelling - Designing and implementing solutions with different data modelling techniques as appropriate.

• Documentation - Anticipating documentation needs for both technical and non-technical audiences, coaching others, and contributes to organizational documentation standards, including in support of knowledge management and data management needs.

• Soft Skills – Communication, Problem Solving, Planning and Prioritization, Critical Thinking

• Incident, Risk and Issue Management - Independently assesses operational risks, applies security policies to mitigate issues, leads strategic incident management, and mentors others for effective response.

• Change Management - Developing and implementing change plans, analyzing culture and readiness, with minimal guidance.

• Agile practices, Data & AI Privacy & Ethics - Effectively participates in Agile teams, adapting to iterative processes and new ways of working. Applying data and AI risk, privacy laws and ethical guidelines to ensure compliance in various data-related activities.

• Testing, Tools & system - Responsible for developing advanced testing methodologies, creating comprehensive strategies, mentoring teams to ensure high-quality deliverables, and applying domain knowledge to independently solve problems and improve systems or processes.

Variation in job grades for the Data Engineer role cover level of expertise, skills and autonomy in the following areas:

• Customer Focus

• Continuous improvement and change

• Problem solving

• Market / Industry knowledge

• Influencing & Relationship Building

• Data Visualisation and story telling

• Modelling/Predictive Analytics skills

• Understanding depth & breadth of data

• Financial/ Business/ Commercial/ Market Acumen

Must Have - Google Cloud Certified - Professional Data Engineer

Area of expertise - SQL, Python, DBT, AWS (LAMBDA) & Google Cloud Platform (GCP) technologies (e.g. Cloud Run, CloudSQL, Google Cloud Storage, BigQuery, Vertex AI)

Mandatory Skill Sets:Google Cloud Certified - Professional Data Engineer Area of expertise -  SQL, Python, DBT,  AWS (LAMBDA) & Google Cloud Platform (GCP) technologies (e.g. Cloud Run, CloudSQL, Google Cloud Storage, BigQuery, Vertex AI)

Preferred Skill Sets:1 Financial Services experience hands-on project experience

Years of Experience required- 7 - 10 years

Education Qualifications:

Degree qualifications in Data Science, Computer Science, Information Technology, Information Systems, Statistics, Applied Mathematics, Business Administration or any other related field