Data Engineer
Horizontal Talent

Job Info

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Job Description:
We are looking for self-motivated, responsive individuals who are passionate about data. You will build data solutions to address complex business questions, taking data through its lifecycle-from the pipeline for data processing and data infrastructure to creating dataset data products.

Core Responsibilities:

• Design and build ETL jobs to support the Enterprise Data Warehouse.
• Write Extract-Transform-Load (ETL) jobs using standard tools.
• Partner with business teams to understand the business requirements, assess the impact on existing systems, and design and implement new data provisioning pipeline processes for Finance/External reporting domains.
• Monitor and troubleshoot operational or data issues in the data pipelines.
• Drive architectural plans and implementations for future data storage, reporting, and analytic solutions.

Qualifications

• 6-8 Years experience in Data Engineering
• 3+ years of experience in implementing big data processing technology: AWS / Azure / GCP, Apache Spark, Python.
• Experience writing and optimizing SQL queries in a business environment with large-scale, complex datasets.
• Working knowledge of higher abstraction ETL tooling (e.g., AWS Glue Studio, Talend, Informatica).
• Detailed knowledge of databases like Oracle, DB2, SQL Server, data warehouse concepts, and technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments.
• Hands-on experience in cloud technologies (AWS, Google Cloud, Azure) related to data ingestion tools (both real-time and batch-based), CI/CD processes, cloud architecture understanding, and big data implementation.
• Must have: DataBricks certification and Azure Cert

NICE TO HAVES:

• AWS certification or experience with
• Working knowledge of Glue, Lambda, S3, Athena, Redshift, Snowflake.
• Strong verbal and written communication skills, excellent organizational and prioritization skills.
• Strong analytical and problem-solving skills

This job has expired.