Data Engineer (Consultants)

Job Title / Primary Skill:

Years of Experience:

Job Location:

Must Have Skills:

Educational Qualification:

Job Overview

As a Data Engineering Consultant, you will be instrumental in designing, developing, and optimizing robust data engineering solutions that support critical business analytics and reporting. You will provide high-quality, timely development and on-time input for service delivery, managed services, or implementation-oriented client projects. Assignments will range from foundational analysis and problem-solving to contributing to the architecture of complex data solutions and potentially leading small technical teams. Your contributions will directly impact client satisfaction objectives. You will also be responsible for developing technical modules and low-level designs while monitoring the technical quality standards of onshore/offshore development teams.

Essential Functions

• Designing and Building Data Warehouse Solutions:

  Design and implement robust ETL/ELT pipelines to process structured and unstructured data. Support the end-to-end design and build of new data warehousing solutions, including understanding intricate business data needs, translating them into technical specifications, and planning for efficient data integration and delivery.

• Requirements Gathering and Data Modelling:

  Conduct in-depth analysis of source systems and business requirements to generate detailed data warehousing specifications, including conceptual, logical, and physical data models. Create comprehensive technical documentation, including design specifications, data flow diagrams, and mapping documents.

• Stakeholder Collaboration:

  Manage internal and external cross-functional stakeholders, including business users, data architects, ETL developers, and BI specialists, to ensure successful data warehouse development and adoption.

• Strategic Data Architecture:

  Develop scalable data architectures using technologies like Spark, Hadoop, and cloud-native tools (AWS, Azure). Leverage deep technical expertise and business acumen to identify strategic alternatives and work with project lead to recommend optimal data warehousing architectures that align with client business goals.

• Knowledge Development:

  Continuously develop a broad knowledge of data warehousing methodologies, industry best practices, and emerging technologies (e.g., cloud data platforms, data lakes) through project delivery and formal/informal learning opportunities.

• Independent and Team Work:

  Work effectively both independently and as a vital part of a technical team, contributing to all phases of the data warehousing lifecycle.

• Client Engagement:

  Attend, support, and present technical solutions and progress updates at client meetings.

• Mentorship and Knowledge Sharing:

  Contribute to the learning, development, and mentoring of junior team members.

Qualifications:

Educational Background:

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related quantitative field.
• Master's Degree in a related field preferred.

Technical Expertise:

• Proven experience in designing, developing, and implementing

  enterprise data warehouses

  using various database technologies (e.g., SQL Server, Oracle, PostgreSQL, Snowflake, Redshift, Azure Synapse).
• Strong proficiency in

  SQL

  and

  Python

• Experience with

  big data

  tools (e.g., Spark, Hadoop, Hive).

Preferred Qualifications:

• Prior work experience in pharmaceutical domain
• Hands-on experience in project management tools (Jira, Asana, Smartsheet, etc.)
• Team management - Experience of leading small project teams (2-3 members)
• Knowledge of Generative AI concepts and tools
• Strong hands-on experience in either of the

  cloud

  platforms - AWS, Azure.
• Understanding of data governance, data quality, and

  master data management

  principles.
• Experience working in Agile / Scrum environments.

Professional Attributes:

• Works willingly and effectively with others in and across the organization to accomplish team goals.
• Knowledge and understanding of the fundamental processes of business, their interaction, and the impact of external/internal influences on decision-making, growth, and decline, specifically as they relate to data strategy.
• Knowledge of consulting methods, tools, and techniques related to data warehousing and business intelligence.
• Knowledge of current events and developments within the data management industry and major competitors.
• Effective time management and project organization skills, with the ability to manage multiple priorities.