About the position
Senior Data Engineer/Analyst - 3 Year Contract
Senior Data Engineer/Analyst - 3 Year Contract
Qualifications & Experience:
Must-Have:
- Bachelors or Masters degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
- 5+ years of experience in data engineering, analytics, or BI development.
- Strong proficiency in SQL and Python for data manipulation and transformation.
- Experience with ETL/ELT processes, data modeling, and data warehousing concepts.
- Expertise in cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Snowflake, Databricks, Kafka).
- Familiarity with data visualization tools (Power BI, Tableau, Looker).
Nice-to-Have:
- Experience with AI/ML model deployment for predictive analytics.
- Knowledge of DevOps for data (CI/CD, Infrastructure-as-Code).
- Certifications in AWS Data Analytics, Azure Data Engineer, or Google Cloud Professional Data Engineer.
Responsibilities: Data Engineering & Architecture:
- Design, develop, and maintain scalable and efficient ETL pipelines for data ingestion, transformation, and storage.
- Build and optimize data warehouses, data lakes, and real-time streaming solutions to support business intelligence and analytics needs.
- Ensure data quality, integrity, and security across all data processing workflows.
- Collaborate with Data Scientists, Analysts, and Software Engineers to design data models that enable advanced analytics.
- Implement data governance, cataloging, and lineage tracking to ensure transparency and compliance.
Data Analysis & Business Intelligence:
- Conduct data exploration, statistical analysis, and trend identification to extract actionable insights.
- Develop interactive dashboards and reports using BI tools like Power BI, Tableau, or Looker.
- Work closely with business teams to understand KPIs and performance metrics, translating data into valuable insights.
- Optimize query performance and database efficiency for large-scale data processing.
Cloud & Big Data Technologies:
- Design and manage cloud-based data solutions (AWS, Azure, GCP) with services such as AWS Glue, Azure Data Factory, Google BigQuery, Snowflake, and Databricks.
- Work with big data frameworks like Apache Spark, Hadoop, or Kafka for distributed data processing.
- Develop automated data pipelines using orchestration tools like Airflow, Prefect, or Luigi.
Collaboration & Leadership:
- Work cross-functionally with engineering, product, and business teams to define data requirements.
- Mentor junior team members and provide guidance on best practices in data engineering and analytics.
- Drive continuous improvement initiatives in data architecture, automation, and AI-driven analytics
Desired Skills:
- Senior
- Data
- Engineer
- Analyst