Data & Analytics Engineer
Accountabilities: The Data & Analytics Engineer will be responsible for developing and maintaining data pipelines, analytics solutions, and reporting capabilities that enable data-driven decision-making. Key responsibilities include:
Own dashboard delivery from development to production, including creating metrics, filters, managing refresh processes, and validating releases.
Build and maintain batch and streaming ETL pipelines using cloud data technologies and distributed processing frameworks.
Develop, optimize, and troubleshoot SQL queries within modern data warehouse environments.
Support near-real-time data ingestion workflows and ensure reliable data movement across systems.
Investigate analytics issues, identify root causes, and communicate findings effectively with technical and business stakeholders.
Monitor data pipelines, dashboards, and workflows to ensure reliability, performance, and availability.
Participate in incident resolution, troubleshooting activities, and root cause analysis.
Develop strong product and business understanding to translate requirements into effective data models and analytics solutions.
Ensure data accuracy, consistency, validation, and governance across multiple data sources.
Collaborate with cross-functional teams to continuously improve analytics capabilities and operational processes.
Requirements:
The ideal candidate is a proactive data professional with strong technical foundations in analytics engineering, cloud platforms, and data visualization. Required qualifications and skills include:
3-4 years of experience in data engineering, analytics engineering, or a related field.
Strong SQL skills, preferably with experience in Redshift or similar modern data warehouse platforms.
Solid programming experience with Python and PySpark for data processing and transformation.
Hands-on experience with AWS data services, including S3, Glue, Redshift, and CloudWatch.
Experience with workflow orchestration tools such as Apache Airflow, including developing, debugging, and deploying DAGs.
Strong understanding of data modeling and data warehousing concepts.
Experience creating BI dashboards using tools such as QuickSight, ThoughtSpot, Tableau, or Power BI.
Ability to quickly understand new products, business contexts, and complex data structures.
Strong problem-solving, communication, and collaboration skills.
Ability to work independently while coordinating effectively with product, engineering, DevOps, and customer-facing teams.
Preferred qualifications include:
Experience with streaming and change data capture technologies such as Kafka, Debezium, or Spark Structured Streaming.
Familiarity with AWS infrastructure concepts including IAM roles, security groups, Secrets Manager, Kinesis, or Firehose.
Experience working with fintech, B2B SaaS, or customer analytics platforms.
Strong awareness of data security, confidentiality, privacy, and responsible handling of sensitive information.
Benefits:
Fully remote work environment.
Full-time employment opportunity.
Opportunity to work on modern cloud-based data platforms and analytics solutions.
Exposure to large-scale data engineering challenges and customer-facing products.
Collaborative environment with cross-functional teams.
Opportunities for professional growth and continuous learning.
Ability to contribute directly to impactful data-driven initiatives.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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