We are looking for a Dyanamic Senior Data Engineer
As a Senior Data Engineer, you will play a pivotal role in shaping the future of data analytics and infrastructure. You will drive key business metrics, collaborate with cross-functional teams, and implement cutting-edge data solutions. This is an exciting opportunity to work with a diverse set of technologies and deliver innovative data products that enhance business outcomes.
Key Responsibilities:
- Data Democratization: Support the goal of democratizing data and data products.
- Analytics & Reporting: Drive audience and behavioral analytics, along with key business metrics using dashboards and reports.
- Cross-Functional Collaboration: Partner with teams such as product engineering, data science, and business stakeholders to achieve business objectives.
- Infrastructure & Technology: Utilize a mix of cloud infrastructure and open-source technologies to build, scale, and maintain data workloads.
- Media Industry Data: Work with data practitioners across various domains including sales, marketing, advertising, engineering, and publications.
- Data Workloads: Design, build, and implement data workloads for both high and low volume data to support business use cases.
- Scalable Data Pipelines: Implement cloud-based, scalable, and reliable data pipelines.
- Data Accuracy: Ensure data workloads are reliable, redundant, and provide accurate, easy-to-use, and timely data.
Required Skills:
- Build and maintain streaming and batch data pipelines.
- Develop transactional and analytical data schemas for data lakes, data warehouses, and data marts.
- Implement Data Analytics and Business Intelligence frameworks to support enterprise data needs.
- Adhere to Data Governance policies throughout the data lifecycle.
- Proficient in datarelated languages and frameworks such as Python, Spark, SQL, Hudi, and Iceberg.
- Propose solutions for data pipelines, data schema, and Business Intelligence dashboards and reports.
- Practice Agile Methodology, particularly Scrum.
- Apply Master Data Management Best Practices and Principles.
- Design Data Models following BI Best Practices like Dimensional Modelling.
Preferred Qualifications:
- Minimum 5 years of handson experience in cloudbased data engineering, business analyst, or solution architect roles.
- Experience with data infrastructure deployments using Terraform Cloud.
- Proficient in version and release management using Git, with knowledge of branching strategies.
- Familiarity with AWS Data and Analytics services such as EMR, Glue, Lambda, Step Functions, Athena, Kinesis, or QuickSight.
- Experience with Business Intelligence Platforms and Tools like Tableau and QuickSight.
- Skilled in using query engines such as Presto on Data Lakes, Data Warehouses, and Data Marts.
- Strong communication skills for conveying Data and Analytics concepts to stakeholders.
