Senior Data Engineer/Analyst
Senior Data Engineer/Analyst
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
Senior Data Engineer/Analyst 3 Year Contract
Qualifications & Experience:
MustHave:
-
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).
NicetoHave:
-
Experience with AI/ML model deployment for predictive analytics.
-
Knowledge of DevOps for data (CI/CD InfrastructureasCode).
-
Certifications in AWS Data Analytics Azure Data Engineer or Google Cloud Professional Data Engineer.
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 realtime 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 largescale data processing.
Cloud & Big Data Technologies:
-
Design and manage cloudbased 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 crossfunctionally 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 AIdriven analytics.
Employment Type
Full Time
