{"id":3977958,"url":"https://alion.io/job/loyalty-juggernaut-inc-analytics-engineer","title":"Analytics Engineer","company":{"id":2930708,"name":"Loyalty Juggernaut, Inc.","domain":"lji.io","url":"https://alion.io/company/lji-io","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"CI/CD","optional":true},{"name":"Dagster","optional":true},{"name":"Databricks","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Python","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-11-09T18:35:35Z","employer_posted_date":null,"last_verified_at":"2026-11-09T18:35:35Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are seeking a skilled and detail-oriented Analytics Engineer with 1-3 years of experience to join our growing Analytics team.\n\nThe ideal candidate will bridge the gap between data engineering and business intelligence by transforming raw data into clean, reliable, well-structured, and reusable analytical datasets. The candidate will be responsible for developing data transformation pipelines, building data models, implementing data quality checks, and optimizing datasets for reporting and analytics.\n\nThis role requires strong SQL skills, experience with data transformation frameworks, an understanding of data warehousing concepts, and the ability to collaborate with Data Engineering, Business Intelligence, Product, and Client teams to deliver trusted data solutions for enterprise loyalty programs.\n\nWhat You'll Do:\nBuild and maintain SQL-based data transformation models to convert raw data into clean, analytics-ready datasets.\nDevelop, test, and optimize data models using SQL, dbt, or similar transformation frameworks.\nDesign dimensional data models, including fact tables, dimension tables, and analytical data marts.\nIntegrate data from multiple sources, including transactional databases, loyalty platforms, APIs, and external systems.\nTranslate business requirements into reusable datasets, standardized metrics, and analytical models.\nDefine and maintain key business metrics related to loyalty performance, customer engagement, points accumulation, reward redemption, and retention.\nImplement data quality checks, validation rules, and reconciliation processes to ensure data accuracy.\nTroubleshoot data discrepancies, monitor pipeline execution, and optimize queries and transformation workflows.\nCollaborate with BI, Data Engineering, Product, and other teams to support dashboards, reporting, and business analytics.\nMaintain data documentation, model dependencies, and transformation logic while following coding, testing, and version control best practices.\n\nWhat We're Looking For:\nBachelor's degree in Computer Science, Engineering, IT, Statistics, Mathematics, or a related field.\n1-3 years of experience in Analytics Engineering, Data Engineering, BI Development, or a similar role.\nStrong SQL skills, including complex joins, CTEs, window functions, aggregations, and query optimization.\nHands-on experience in data transformation, data modelling, and building analytics-ready datasets.\nUnderstanding of data warehousing, dimensional modelling, star schemas, fact tables, and dimension tables.\nFamiliarity with dbt, SQL-based ETL/ELT frameworks, and data pipeline concepts.\nExperience with relational databases, data validation, testing, and version control tools such as Git.\nStrong analytical, problem-solving, and debugging skills.\nAbility to translate business requirements into scalable data solutions and collaborate with cross-functional teams.\n\nGood to Have:\nExperience with Snowflake, Google BigQuery, Amazon Redshift, or Databricks.\nHands-on experience with dbt models, tests, macros, and documentation.\nBasic to intermediate Python skills for data processing and automation.\nFamiliarity with Apache Airflow, Dagster, or similar orchestration tools.\nExposure to cloud data warehouses, data lakehouse architectures, and CI/CD practices.\nExperience working with large-scale customer, transactional, or event-driven datasets.\nFamiliarity with CRM, CDP, enterprise SaaS, or customer loyalty platforms.\nUnderstanding of loyalty concepts such as reward points, customer tiers, redemption, and customer engagement.\n\nKey Competencies:\nSQL & Query Optimization\nAnalytics Engineering & Data Transformation\nData Modelling & Warehousing\ndbt & ELT Development\nData Quality & Automated Testing\nCloud Data Platforms\nData Integration & Pipeline Development\nDocumentation & Version Control\nAnalytical Problem Solving\nCross-Functional Collaboration\n\nKey Performance Indicators (KPIs):\nAccuracy and reliability of analytical datasets.\nQuality and performance of data models and SQL queries.\nReduction in data discrepancies and reporting inconsistencies.\nTimely availability of data for reporting and analytics.\nEffectiveness of automated testing and data quality checks.\nReduction in manual data preparation efforts.\nAdherence to documentation and coding standards.\nSkills\nDWH, ELT, ETL, SQL, dbt","description_format":"text","description_chars":4321,"description_truncated":false,"requirements":{"experience_years_min":1,"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":["Artificial Intelligence","Gift Cards & Loyalty Programs","AI Agents"],"lifecycle":[{"event":"open","at":"2026-11-09T18:35:35Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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