{"id":3546168,"url":"https://alion.io/job/spin-ic3-data-engineer","title":"IC3 - Data Engineer","company":{"id":1811024,"name":"Spin","domain":"spin.app","url":"https://alion.io/company/spin-app","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":6,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":23,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":81000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1015},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Dask","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-30T19:40:56Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-10-31T05:04:08Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Objective of the Role\nResponsible for designing, developing, and maintaining robust data pipelines and architectures that support the organization’s data-driven initiatives. This role contributes to all phases of the data engineering lifecycle, ensuring scalability, reliability, and performance. Demonstrates technical leadership by solving complex problems, mentoring junior engineers, and actively improving data engineering practices.\nMain Responsibilities\nDesign and implement scalable and efficient data pipelines for ingesting, processing, and storing structured and semi-structured data from diverse sources.\nCollaborate with stakeholders to gather requirements, identify data sources, and define the feasibility of requested solutions.\nDevelop and optimize ETL processes, ensuring the accuracy, consistency, and integrity of data throughout its lifecycle.\nCreate and maintain data models, adhering to best practices for normalization and performance optimization.\nBuild and manage cloud-based data architectures, including data lakes, data warehouses, and real-time streaming solutions.\nImplement monitoring and alerting systems to ensure the reliability and performance of data pipelines in production.\nContribute to data governance initiatives by ensuring data quality, security, lineage, and compliance with relevant regulations.\nUtilize advanced data processing frameworks like Apache Spark, Apache Kafka, and Flink for batch and real-time data processing.\nMaintain and enhance CI/CD pipelines to automate data engineering workflows and ensure seamless deployment.\nPerform code reviews and enforce coding standards to ensure quality and maintainability.\nDocument processes, architectures, and technical workflows to support knowledge sharing and operational continuity.\nMentor junior engineers, sharing expertise and fostering a collaborative team environment.\nIdentify opportunities for process optimization and automation to improve efficiency and reduce manual effort.\nCollaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver impactful data solutions.\nPromote an autonomous work culture by encouraging self-management, accountability, and proactive problem-solving among team members.\nServe as a Spin Culture Ambassador to foster and maintain a positive, inclusive, and dynamic work environment that aligns with the company's values and culture.\nRequired Knowledge and Experience\nMinimum 3 - 4 years of experience as a Data Engineer\nIn-depth understanding of core data engineering concepts and principles, including complex ETL (Extract, Transform, Load) processes, scalable data pipelines, and advanced data warehousing techniques.\nAdvanced proficiency in Python, including writing efficient and optimized code, using advanced features like decorators, generators, and context managers.\nExtensive experience with Python libraries and frameworks commonly used in data engineering, such as Pandas, NumPy, PySpark, and Dask.\nStrong knowledge of both SQL and NoSQL databases, including advanced querying, indexing, and optimization techniques.\nExperience with database design, normalization, and performance tuning.\nAdvanced understanding of data modeling concepts and techniques, including star schema, snowflake schema, and dimensional modeling.\nExperience with data modeling tools and best practices.\nProficient in various data processing methods, including batch processing, stream processing, and realtime data processing.\nExtensive experience with data processing frameworks like Apache Spark, Apache Kafka, and Apache Flink.\nAdvanced knowledge of file processing concepts, including handling large datasets and working with different file formats (e.g., CSV, JSON, Parquet, Avro).\nStrong understanding of data governance principles, including data quality management, data lineage, data security, and data privacy.\nComprehensive understanding of the end-to-end data engineering lifecycle, including data ingestion, transformation, storage, and retrieval.\nExperience with CI/CD pipelines and automation for data engineering workflows.\nAdvanced understanding of various data architectures, including data lakes, data warehouses, data marts, and data mesh.\nExperience designing and implementing scalable and robust data architectures.\nProficient with version control systems (e.g., Git) and experience managing code repositories on platforms like GitHub or GitLab.\nAdvanced understanding of data visualization tools (e.g., Tableau, Power BI) and reporting techniques.\nAbility to create insightful and impactful visualizations and dashboards.\nStrong understanding of cloud computing in AWS and GCP stacks.\nBasic experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation.\nProven experience leading projects with Objectives and Key Results (OKRs), identifying risks, and delivering significant business value.\nAbility to mentor and guide junior data engineers.\nStrong ability to communicate project status transparently, including progress, challenges, and next steps.\nEffective collaboration with cross-functional teams, including data scientists, analysts, and business \nstakeholders\nEn Spin estamos comprometidos con construir un lugar de trabajo diverso e inclusivo.\nCreemos en la igualdad de oportunidades y promovemos un entorno libre de discriminación por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad o cualquier otra condición legalmente protegida.","description_format":"text","description_chars":5512,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Payment Processing & Gateways","Digital Banks & Neobanks"],"lifecycle":[{"event":"open","at":"2026-10-30T20:48:58Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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