Sr. Data Engineer - #944 en Economicmodeling

The Senior Data Engineer will be responsible for designing, building, and maintaining the data infrastructure that supports analytics, machine learning, and enterprise decision-making. This role will lead the development of scalable big data frameworks, translate complex business and technical requirements into detailed architectural solutions, and deliver high-performing software that drives measurable outcomes.Key responsibilities include selecting and implementing data solutions, defining hardware and system requirements, and establishing standards and processes for integration projects and initiatives.The ideal candidate will bring deep SQL expertise and strong software engineering discipline to ensure the reliability, scalability, and quality of data pipelines. In addition to technical execution, the Senior Data Engineer will collaborate closely with engineering, analytics, and product teams, mentor junior engineers, and play a pivotal role in shaping the organization’s technical roadmap.

Major Responsibilities:

Architect, build, and maintain scalable, reliable data pipelines (batch & streaming) to ingest, transform, and deliver data for analytics, reporting, and ML use cases.

Architect software applications, test, and build automated tools.

Translate complex functional and technical requirements into architecture designs and high-performing software solutions.

Select appropriate data solution software and define hardware requirements to support performance and scalability.

Develop and implement standards and processes for data integration projects and initiatives.

Lead the design and development of software applications, testing, and building tools.

Optimize SQL queries (joins, window functions, aggregations, partitioning, indexing) and data schema performance.

Design data models, schemas, and data warehouses/data lakes (dimensional, star, snowflake schemas, normalization/denormalization).

Ensure data quality, correctness, and consistency across datasets (validation, anomaly detection, reconciliation).

Ensure database changes are reviewed and approved according to standards.

Monitor, troubleshoot, and tune performance of pipelines, databases, and workloads.

Drive adoption of engineering best practices: version control, CI/CD, testing (unit and integration for data pipelines), documentation, and code reviews.

Collaborate with software engineers to integrate data systems into production environments.

Provide technical assistance to junior members and to colleagues across the company.

Mentor and coach junior and mid-level engineers, promoting engineering discipline across the team.

Evaluate and propose new tools, frameworks, and technologies for the data platform.

Ensure data security, governance, access control, lineage, and compliance (e.g., GDPR, CCPA, internal standards).

Education and Experience:

Bachelor’s degree in Computer Science or a related technical discipline (Master’s preferred)

5+ years of professional experience in data engineering, software engineering, or data science

Expert-level SQL, including query optimization, advanced joins, windowing, partitioning, and indexing

Proven expertise in Snowflake for data warehousing and advanced analytics

Strong background in data modeling, data engineering best practices, and distributed systems (e.g., Spark, Hadoop, Hive, Presto)

Hands-on experience designing and maintaining ETL/ELT pipelines, data integration (APIs, event streams, logs), and workflow orchestration (Airflow or Astronomer required)

Proficiency with modern data stack tools, including DBT for transformation and modeling

Experience with AWS cloud services for data engineering and infrastructure management

Strong software engineering skills, including clean code practices, modularization, error handling, logging, CI/CD, and automated testing

Knowledge of object-oriented design, data structures, algorithms, and disaster recovery strategies for data systems

Skilled in scalability and performance optimization across pipelines, databases, and workloads

Familiarity with Python (preferred) and other modern programming languages

Demonstrated ability to analyze complex data sets, identify trends, and derive actionable insights

Effective collaborator with cross-functional teams and proven success in mentoring junior engineers

Experience with agile or rapid application development methodologies

Highly creative, detail-oriented, and results-driven with strong problem-solving and prioritization skills

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