Data Engineer
Summary
Designs and maintains data pipelines, warehouses, and analytics infrastructure using SQL, Python, and AWS services to support reporting and modeling for clients.
On-site - Pasay 3-5 Yrs Exp Bachelor Full-time
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Job Description
Government Mandated Benefits
Insurance Health & Wellness
Health Insurance
Qualifications for Data Engineer/Operations
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with structured and unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience in retail and its business metrics is a plus.
We are looking for a candidate with 3+ years of experience in a Data Engineer/Operations role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Experience with ETL/ELT tools: AWS Glue, Informatica, Talend, etc.
Optional
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Responsibilities:
- Designing, developing, and modifying data infrastructure to accelerate the processes of data analysis and reporting.
General Duties
- Analyzing and organizing raw data
- Building data systems and pipelines
- Evaluating business needs and objectives
- Interpreting trends and patterns
- Preparing data for descriptive, prescriptive and predictive modeling
- Building algorithms and prototypes
- Developing analytical tools and programs
- Collaborating with data analyst, data scientists and architects on projects
Detailed Duties
- Analysis and profiling in preparation for data ingestion to data lake
- Develop, maintain and monitor ETL/ELT jobs
- Analysis and preparation of data models for the data warehouse
- Develop, maintain and monitor SQL queries
- Analysis and preparation of descriptive, prescriptive or predictive analytics
- Document, optimized and maintain existing data pipelines