Data Engineer

SLI Consulting Inc.; Pasay; On-site; PHP 669,600 - 1,004,400; Full time

Benefits offered by this job

Health Insurance

Government Mandated Benefits

Job summary

A consulting company is seeking a Data Engineer with 3+ years of experience and a graduate degree in a quantitative field. The primary responsibilities include designing and developing data infrastructure, analyzing raw data, and collaborating with data analysts and scientists. The candidate should have advanced SQL knowledge, strong analytic skills, and familiarity with various databases and data pipeline tools. This is an on-site position located in Pasay, Metro Manila, offering a full-time contract.

Qualifications

• 3+ years of experience in a Data Engineer/Operations role.
• Experience with data pipeline and workflow management tools.
• Experience supporting cross-functional teams.

Responsibilities

• Design and develop data infrastructure.
• Analyze and organize raw data.
• Collaborate with data analysts and scientists.

Skills

Advanced SQL knowledge

Strong analytic skills

Project management skills

Experience in retail metrics

Education

Graduate degree in a quantitative field

Tools

Postgres

Cassandra

AWS EC2

AWS EMR

AWS RDS

AWS Redshift

Python

Java

C++

Scala

AWS Glue

Informatica

Talend

Hadoop

Spark

Kafka

Storm

Spark-Streaming

Job description

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

1. Analyzing and organizing raw data
2. Building data systems and pipelines
3. Evaluating business needs and objectives
4. Interpreting trends and patterns
5. Preparing data for descriptive, prescriptive and predictive modeling
6. Building algorithms and prototypes
7. Developing analytical tools and programs
8. Collaborating with data analyst, data scientists and architects on projects

Detailed Duties

1. Analysis and profiling in preparation for data ingestion to data lake
2. Develop, maintain and monitor ETL/ELT jobs
3. Analysis and preparation of data models for the data warehouse
4. Develop, maintain and monitor SQL queries
5. Analysis and preparation of descriptive, prescriptive or predictive analytics
6. Document, optimized and maintain existing data pipelines