{"id":1946918,"url":"https://alion.io/job/synechron-data-engineeranalyst-python-spark-sql-cloud-data-architecture","title":"Data Engineer/Analyst – Python, Spark, SQL, Cloud & Data Architecture","company":{"id":5306,"name":"Synechron","domain":"synechron.com","url":"https://alion.io/company/synechron","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":97,"open_postings":12,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-10-06T05:45:30Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":15500,"max_usd":31000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":54},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"MySQL","optional":false},{"name":"Oracle","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-10-06T07:26:51Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-06T18:13:39Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Summary\nSynechron is seeking a Lead - Data Engineer/Data Analyst to lead Data and Analytics projects and deliver data-driven solutions. The role will combine technical expertise in data engineering, analytics, data architecture, modeling, integration, visualization, and governance with project delivery and team leadership responsibilities. The successful candidate will work closely with clients and internal teams to understand business requirements, design effective data solutions, manage delivery plans, and ensure projects are completed on time, within budget, and to agreed quality standards. The role will contribute to business value through reliable data, actionable insights, scalable architectures, and improved decision-making.\nSoftware Requirements\nRequired\nSQL: Strong experience with data analysis, data transformation, querying, validation, and database development.\nPython: Strong experience in data engineering, analytics, automation, or data processing.\nApache Spark: Strong experience with distributed data processing and large-scale data workloads.\nDatabase technologies: Experience with Oracle, MySQL, and SQL Server.\nData warehousing: Strong understanding of data warehouse architecture, modeling, and implementation.\nData lakes: Experience with data lake concepts, data ingestion, storage, processing, and governance.\nBig data platforms: Strong technical understanding of platforms supporting large-scale data processing and analytics.\nData modeling: Experience designing conceptual, logical, and physical data models.\nData integration: Experience designing and implementing data integration solutions.\nData governance: Experience with data quality, standards, ownership, metadata, access, and lifecycle controls.\nData visualization and BI: Knowledge of Tableau and Power BI.\nCloud data solutions: Familiarity with AWS and Azure data environments.\nProject delivery tools: Ability to use tools for project planning, delivery schedules, documentation, collaboration, and reporting.\nPreferred\nExperience with cloud-native data architectures and data engineering services.\nExperience delivering data-driven solutions in complex enterprise environments.\nExperience with data quality automation, metadata management, lineage, and reconciliation.\nExperience with advanced analytics, reporting, or self-service BI solutions.\nCertification in data engineering, analytics, cloud, database, or BI technologies.\nExperience improving data-processing efficiency and optimizing cloud resource usage.\nOverall Responsibilities\nLead and manage Data and Analytics projects from requirements definition through delivery and transition.\nWork closely with clients and internal stakeholders to understand business requirements and develop data-driven solutions.\nProvide technical expertise and guidance to junior team members and project teams.\nOversee data collection, cleansing, transformation, validation, and preparation processes.\nDesign and implement data architectures, data models, data warehouses, data lakes, and data integration solutions.\nDevelop and maintain project plans, delivery schedules, milestones, dependencies, risks, and resource plans.\nLead data analysis and modeling activities to address business and analytical requirements.\nGuide the selection and application of data technologies, tools, platforms, and delivery approaches.\nEnsure data solutions meet requirements for quality, scalability, maintainability, security, and performance.\nLead technical discussions with clients, architects, analysts, engineers, and other stakeholders.\nReview technical outputs, data models, integration designs, analytical solutions, and project deliverables.\nMonitor project progress, quality, budget, risks, and delivery timelines.\nMentor team members and support knowledge sharing, technical development, and consistent engineering practices.\nEnsure project deliverables are completed on time, within budget, and in accordance with agreed standards.\nPromote efficient use of data storage, processing, and cloud resources to support sustainable technology practices.\nTechnical Skills (By Category)\nProgramming Languages\nEssential\nPython.\nSQL.\nApache Spark development and data-processing capabilities.\nAbility to write maintainable code for data transformation, validation, automation, and analytics.\nExperience applying programming and query techniques to large-scale data workloads.\nPreferred\nExperience with additional scripting or programming languages used for data engineering, automation, or analytics.\nExperience developing reusable data-processing frameworks, utilities, or automation components.\nDatabases/Data Management\nEssential\nOracle.\nMySQL.\nSQL Server.\nData warehousing.\nData lakes.\nBig data platforms.\nData modeling and data integration.\nData collection, cleansing, preparation, transformation, and validation.\nData governance and data quality management.\nUnderstanding of data structures, relationships, lineage, ownership, access, and lifecycle management.\nPreferred\nExperience with data migration, reconciliation, metadata management, lineage, and master data practices.\nExperience with database and data-platform performance optimization.\nExperience designing data solutions for high-volume or complex analytical workloads.\nCloud Technologies\nEssential\nFamiliarity with cloud-based data solutions.\nAWS.\nAzure.\nUnderstanding of cloud data storage, processing, integration, scalability, availability, and governance considerations.\nPreferred\nExperience designing or implementing cloud-native data architectures.\nExperience with cloud data warehouses, data lakes, processing platforms, and integration services.\nExperience with cloud monitoring, cost management, resource optimization, and sustainable data-processing practices.\nExperience supporting cloud migration or data-platform modernization.\nFrameworks and Libraries\nEssential\nApache Spark.\nFrameworks and libraries used for Python-based data engineering and analytics.\nComponents supporting data ingestion, transformation, validation, integration, and analytics.\nTools supporting data visualization and business intelligence, including Tableau and Power BI.\nPreferred\nLibraries supporting advanced analytics, data quality, profiling, lineage, and workflow automation.\nReusable data-engineering components and shared analytical frameworks.\nTools supporting self-service reporting and interactive data exploration.\nDevelopment Tools and Methodologies\nEssential\nData and Analytics project delivery.\nProject planning and delivery scheduling.\nRequirements analysis and solution design.\nData architecture and modeling.\nData integration and pipeline development.\nData governance and quality practices.\nClient and stakeholder collaboration.\nTechnical reviews and delivery reporting.\nTeam leadership, mentoring, and project coordination.\nAbility to manage multiple tasks, priorities, dependencies, risks, and deliverables.\nPreferred\nAgile delivery methodologies.\nProject portfolio management and governance practices.\nAutomated data-quality checks, testing, monitoring, and deployment.\nExperience with source control, CI/CD, workflow orchestration, and data pipeline monitoring.\nExperience establishing data engineering standards and delivery metrics.\nSecurity Protocols\nEssential\nApply data security and governance practices throughout data collection, storage, processing, integration, and reporting.\nProtect sensitive business and client data through appropriate access controls, permissions, and secure handling practices.\nConsider data privacy, retention, classification, lineage, and auditability requirements in solution design.\nIdentify and escalate security, privacy, data-quality, and operational risks.\nPreferred\nExperience implementing security controls in cloud-based data platforms.\nExperience supporting regulatory, audit, privacy, or compliance requirements.\nExperience with data masking, encryption, role-based access, and secure data integration.\nExperience incorporating security and governance checks into data delivery processes.\nExperience Requirements\nRequired: Minimum of 7 years of experience in Data and Analytics projects.\nExperience leading project teams and managing project delivery.\nProven track record of delivering data-driven solutions to clients.\nStrong experience with Python, Apache Spark, SQL, data warehousing, data lakes, big data platforms, data modeling, and data integration.\nExperience with Oracle, MySQL, SQL Server, Tableau, Power BI, AWS, and Azure is required or preferred according to the specific project scope.\nExperience managing project plans, delivery schedules, technical discussions, quality, budgets, risks, and stakeholder expectations.\nExperience mentoring junior team members and providing technical guidance.\nIndustry-specific experience is not mandatory; experience delivering data solutions in complex enterprise environments is preferred.\nCandidates may also qualify through an equivalent combination of relevant data engineering, data analytics, project leadership, client delivery, technical training, and demonstrated delivery outcomes.\nDay-to-Day Activities\nLead data analysis, modeling, architecture, integration, and solution-design activities while working with clients to understand data needs.\nManage project delivery through planning, scheduling, progress tracking, risk management, stakeholder coordination, and budget monitoring.\nLead technical discussions with clients and internal teams and provide guidance on data platforms, models, governance, quality, and integration approaches.\nMentor team members, review deliverables, ensure quality and timely delivery, and make technical decisions within agreed project standards.\nQualifications\nA bachelor’s or master’s degree in Computer Science, Information Systems, Engineering, or a related field is required; equivalent relevant education and experience may be considered.\nMinimum of 7 years of experience in Data and Analytics projects, including project leadership and delivery management.\nDemonstrated experience with Python, Apache Spark, SQL, databases, data modeling, data integration, data warehousing, data lakes, and big data platforms.\nCertifications in data engineering, analytics, cloud platforms, databases, BI, or related technologies are preferred but not mandatory.\nMaintain continuous professional development in data engineering, analytics, cloud platforms, data governance, visualization, project delivery, and emerging data technologies.\nProfessional Competencies\nApply structured analytical thinking and problem-solving to assess data requirements, resolve data issues, and design practical solutions.\nLead project teams, mentor junior team members, and provide technical guidance across data engineering and analytics activities.\nCommunicate data concepts, technical decisions, risks, progress, and recommendations clearly to clients and internal stakeholders.\nAdapt to evolving business requirements, data technologies, delivery priorities, project constraints, and client needs.\nIdentify opportunities to improve data quality, automation, architecture, analytics, delivery efficiency, and sustainable resource utilization.\nManage multiple projects, priorities, dependencies, delivery schedules, budgets, stakeholder expectations, and team workloads effectively.\nS YNECHRON’S DIVERSITY & INCLUSION STATEMENT\nDiversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. 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