Data Engineer
7 days ago
About CX Data Labs: At CX Data Labs, we believe that by systematically understanding and adapting to changing customer preferences, companies can sustainably grow their business. We help our clients realize this vision through our advisory and implementation services in Digital, Data, and Analytics competencies, bridging the gap between Strategy and Execution.
Our secret sauce is our team of highly skilled and knowledgeable "Craftsmen" who are constantly expanding their expertise by participating in industry-shaping initiatives. With our systematic problem-solving approaches and deep technology, data, and analytics expertise, we're leading the charge in driving business success through the refinement of customer-centric processes.
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:
5+ years of relevant work experience in data engineering or software engineering equivalent.
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 realtime and batch-based), CI/CD processes, cloud architecture understanding, and big data implementation.
Preferred Skills:
AWS certification or experience with cloud technologies.
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.
Databricks and Azure certification
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