The Data Intelligence engineer is responsible for designing and optimizing the organization's enterprise data ecosystem. This role ensures that data structures, models, and platforms are scalable, secure, and aligned with business needs, enabling advanced analytics and data-driven decision-making. Also, should take whole ownership on Design and maintain enterprise data models, schemas, and metadata frameworks by ensuring data quality, consistency, and governance across systems. Should be able to evaluate and recommend modern data platforms, tools, and technologies.

Essential Job Duties :

1. Data Architecture and Engineering :

- Support the Design and implementation of scalable data Lakehouse architectures to support advanced analytics and reporting.

- Optimize data workflows and ETL processes using DataStage for seamless data integration and transformation.

- Ensure data quality, integrity, and security across all systems.

2. Advanced Analytics and Reporting :

- Develop and maintain interactive dashboards and reports using Power BI and Cognos.

- Collaborate with business stakeholders to understand reporting requirements and deliver actionable insights.

- Enable self-service analytics by empowering users with intuitive dashboards and tools.

3. Tool-Specific Expertise :

- Data Lakehouse : Hands-on experience in designing and implementing data Lakehouse solutions (e.g., Dremio, Databricks, Snowflake, or similar).

- Power BI : Create visually compelling and interactive dashboards to support business decision-making.

- Airflow : Able to design workflow orchestrations on platform like airflow.

- Python : Able to write python scripts and able to user libraries like NumPy, Pandas, data frames, csv, matplotlib, scikit-learn, etc.

- PySpark : Able to write Python API for Apache Spark, used to process and analyze massive datasets across distributed clusters and perform optimization on pyspark scripts.

- Cognos : Design and deploy enterprise-grade reports and analytics solutions using IBM Cognos.

- DataStage : Develop and optimize ETL workflows using IBM DataStage for seamless data integration.

4. Delivery :

- Handle end-to-end delivery of data projects, ensuring they are completed on time and within budget.

- Prioritize tasks, allocate resources, and communicate project status to stakeholders.

5. Collaboration and Stakeholder Engagement :

- Work closely with business leaders, BA's, Data Dev/Data Ops Teams and US partners to align data initiatives with organizational goals.

6. Innovation and Continuous Improvement :

- Stay updated on emerging trends and best practices in data engineering, Data Intelligence, analytics, and BI tools.

- Identify opportunities to optimize data processes and improve team efficiency.

Basic Qualifications Education & Experience :

- Bachelor's (OR) Master's degree in computer science, Data Science, Engineering, or a related field.

- 8 + years of experience in data engineering, data Intelligence, analytics, or BI roles.

- Proven hands-on experience with data Lakehouse architecture, Cognos, Power BI, and DataStage, Airflow, PySpark, Python.

Preferred Qualifications :

- Proficiency in scripting languages (e.g., Python, Shell).

Knowledge/Skills/Abilities :

- Data Lakehouse : Proficient in handling the designing and implementing data Lakehouse solutions (e.g., either one of Dremio, Databricks, Snowflake, or similar).

- Cognos : Proficiency in designing and deploying reports and dashboards.

- Power BI : Strong skills in creating interactive visualizations and dashboards.

- IBM DataStage : Hands-on experience in developing and optimizing ETL workflows.

- TSQL : Strong knowledge in T-SQL development and optimization.

- Python : Strong knowledge in Python script development.

- PySpark : Strong understanding of Apache Spark with the ability to implement and optimize PySpark scripts.

- Excellent communication and interpersonal skills.

- Strong problem-solving and analytical thinking abilities.

- Ability to manage multiple priorities in a fast-paced environment.

Essential Physical Demands/Work Environment :

- Work is primarily sedentary : must be able to sit for extended periods of time and use a computer, keyboard, and mouse, frequently. The employee must occasionally lift and/or move up to 50 pounds.

- Travel may be required periodically, including overnight stays (contingent on position requirements).