{"id":3104742,"url":"https://alion.io/job/convosight-data-engineer-product-manager","title":"Data Engineer - Product Manager","company":{"id":9316,"name":"Convosight","domain":"convosight.com","url":"https://alion.io/company/convosight","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Product","role_family":"Product","seniority":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":28000,"period":"year","method":"role_seniority_country_cell","sample_n":19},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true}],"status":"live","first_seen_at":"2026-10-22T18:35:15Z","employer_posted_date":null,"last_verified_at":"2026-10-22T18:35:15Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We are looking for a Data Engineer - Product Manager who thrives at the intersection of data engineering and product strategy. This is a hands-on role for someone who can build reliable data pipelines and use data-driven insights to influence product decisions. You'll own the process end-to-endfrom ingesting and transforming data to defining metrics, identifying opportunities, and recommending what should be built next. If you're looking for clearly defined handoffs between engineering and product, this isn't the role for you.\n\nResponsibilities: \nDesign, build, and maintain scalable, reliable data pipelines using modern data engineering tools.\nEnsure data quality, integrity, and reliability across ingestion, transformation, and reporting.\nAnalyse data to identify product opportunities, customer insights, and business trends.\nTranslate complex data into actionable product recommendations for stakeholders.\nDefine meaningful product metrics and establish data-driven success criteria.\nPartner closely with engineering, product, and business teams to drive product decisions.\nDevelop automated validation, monitoring, and alerting systems to improve pipeline reliability.\nUse AI-assisted tools to accelerate development while maintaining engineering quality.\nContinuously evaluate data sources, identify risks, and improve data accuracy.\nTake ownership of the complete lifecyclefrom raw data to product decisions.\n\nData Engineering: \nBuild and optimise ETL/ELT pipelines.\nIntegrate multiple structured and unstructured data sources.\nMaintain scalable data infrastructure.\nMonitor pipeline performance and resolve production issues.\nImplement automated data quality checks and monitoring.\n\nProduct Management: \nIdentify business problems using data.\nPrioritise features based on measurable customer impact.\nDefine hypotheses, success metrics, and evaluation plans.\nRecommend product improvements backed by quantitative analysis.\nPresent clear recommendations to stakeholders.\n\nRequirements: \nExperience in both Data Engineering and Product Management.\nStrong SQL and database expertise.\nExperience building production-grade data pipelines.\nKnowledge of Python or other data engineering languages.\nFamiliarity with modern cloud data platforms and ETL tools.\nStrong analytical and problem-solving skills.\nAbility to define KPIs and product success metrics.\nExperience working with dashboards and data visualisation tools.\nExcellent communication and stakeholder management skills.\nStrong ownership mindset with the ability to work independently.\n\nPreferred Experience: \nExperience using AI-assisted development tools.\nExposure to product analytics and experimentation.\nExperience with cloud platforms (AWS, Azure, or GCP).\nFamiliarity with data warehousing technologies.\nStartup or fast-paced product environment experience.\n\nGood to Have: \nStrong ownership and accountability.\nExcellent product judgment backed by data.\nClose attention to detail and engineering rigour.\nAbility to balance speed with quality.\nComfortable making decisions with incomplete information.\nPassion for building products that solve real customer problems.\nSelf-driven, proactive, and execution-focused.\nSkills\nELT, ETL, Python, SQL, data pipeline, data pipelines, pipeline, 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