Collins Aerospace (RTX) is Hiring Associate Engineer - Data Analytics | Bangalore | Freshers

Job Description

Collins Aerospace's Associate Engineer opening is worth a closer look for one distinctive reason: it's a 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐫𝐨𝐥𝐞 𝐞𝐱𝐩𝐥𝐢𝐜𝐢𝐭𝐥𝐲 𝐨𝐩𝐞𝐧 𝐭𝐨 𝐧𝐨𝐧-𝐂𝐒 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐛𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝𝐬 — Mechanical, Industrial, Production, and Aerospace engineering graduates are listed alongside Computer Science and IT as eligible, which is unusual for a data-focused position. This makes it a genuinely interesting option for mechanical/industrial engineering graduates who've developed an interest in data analytics but don't want to fully pivot away from their core engineering domain — you'd be applying data skills directly within a manufacturing and aerospace context rather than a generic tech company setting.

RTX (Collins Aerospace's parent) is the world's largest aerospace and defense company, which shapes what this role actually looks like day-to-day: expect 𝐫𝐞𝐠𝐮𝐥𝐚𝐭𝐞𝐝, 𝐬𝐚𝐟𝐞𝐭𝐲-𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐦𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 (quality metrics, supplier performance, operational KPIs) rather than typical business analytics like marketing or sales data. Worth flagging directly: this posting explicitly states 𝐛𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝 𝐜𝐡𝐞𝐜𝐤𝐬 𝐚𝐧𝐝 𝐝𝐫𝐮𝐠 𝐬𝐜𝐫𝐞𝐞𝐧𝐢𝐧𝐠 𝐚𝐫𝐞 𝐦𝐚𝐧𝐝𝐚𝐭𝐨𝐫𝐲 for all India hires — a detail some candidates might not expect for a data analytics role, and worth being prepared for as part of the process.

The role's real technical center is 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝 𝐚𝐧𝐝 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐮𝐬𝐢𝐧𝐠 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐭𝐨𝐨𝐥𝐬, 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈, 𝐚𝐧𝐝 𝐓𝐚𝐛𝐥𝐞𝐚𝐮, applied to Lean/Six Sigma-style continuous improvement initiatives — meaning the analytics skills here are explicitly tied to manufacturing process improvement methodologies, not abstract data science. For most engineering graduates, the biggest gap to close before applying isn't the analytics tools themselves (Excel, Power BI, and Tableau are increasingly covered in coursework or easily self-taught) but genuine familiarity with 𝐋𝐞𝐚𝐧/𝐒𝐢𝐱 𝐒𝐢𝐠𝐦𝐚/𝐊𝐚𝐢𝐳𝐞𝐧 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬, which are typically industrial engineering-specific and less commonly covered outside that discipline.

𝐎𝐮𝐫 𝐓𝐚𝐤𝐞:

- 𝐆𝐨𝐨𝐝 𝐟𝐨𝐫: engineering graduates (mechanical, industrial, aerospace, or CS/IT) with basic data visualization skills who want to apply analytics within a manufacturing/aerospace domain rather than a pure tech company setting

- 𝐍𝐨𝐭 𝐢𝐝𝐞𝐚𝐥 𝐟𝐨𝐫: those uncomfortable with mandatory background checks/drug screening, or seeking a purely software-engineering-focused data role

- 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲: moderate — the broad degree eligibility widens the applicant pool considerably, but genuine exposure to Power BI/Tableau and some Lean/Six Sigma familiarity (even basic coursework-level) will likely differentiate candidates meaningfully

- 𝐂𝐚𝐫𝐞𝐞𝐫 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲: commonly leads into Data Analyst, Process Improvement Engineer, or Business Intelligence Analyst roles, with aerospace/defense-sector data experience being a distinctive credential given the industry's strict regulatory and quality standards

𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: Collins Aerospace hasn't disclosed base pay, though the listing does detail a notable benefits package including group life/health/accident insurance, 18 vacation days, a pension scheme, and fuel/driver allowances. Based on general market data for Associate Engineer-level data analytics roles at large aerospace/defense manufacturers in Bangalore, base compensation typically ranges around ₹4.5–6.5 LPA for freshers — this is an estimate only, and the comprehensive benefits package mentioned could meaningfully affect total compensation value beyond base salary.

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: Given the broad engineering-discipline eligibility, if you're coming from a non-CS background (mechanical, industrial, aerospace), specifically highlight any academic project, internship, or coursework where you used Excel, Power BI, or Tableau for data analysis — this listing is unusually welcoming of engineering generalists who've built data skills as a secondary competency, so making that overlap explicit in your application is likely to stand out more than presenting yourself as either "purely mechanical" or "purely data."

Roles & Responsibilities

The responsibilities center on being the data backbone for cross-functional manufacturing reviews — collecting and standardizing data, then translating it into dashboards and insights that Quality, Engineering, Manufacturing, and Supply Chain teams can act on, tied directly to continuous improvement initiatives.

- 𝐂𝐨𝐥𝐥𝐞𝐜𝐭, 𝐯𝐚𝐥𝐢𝐝𝐚𝐭𝐞, 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐢𝐳𝐞, 𝐚𝐧𝐝 𝐦𝐚𝐢𝐧𝐭𝐚𝐢𝐧 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐚𝐧𝐝 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐝𝐚𝐭𝐚 across business systems

- 𝐏𝐚𝐫𝐭𝐧𝐞𝐫 𝐰𝐢𝐭𝐡 𝐐𝐮𝐚𝐥𝐢𝐭𝐲, 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠, 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠, 𝐒𝐮𝐩𝐩𝐥𝐲 𝐂𝐡𝐚𝐢𝐧, 𝐚𝐧𝐝 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 𝐭𝐞𝐚𝐦𝐬 for leadership reviews

- 𝐃𝐞𝐯𝐞𝐥𝐨𝐩 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 𝐚𝐧𝐝 𝐊𝐏𝐈 𝐫𝐞𝐩𝐨𝐫𝐭𝐬 using Microsoft Tools, Power BI, and Tableau

- 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝐭𝐫𝐞𝐧𝐝𝐬 across quality, manufacturing, supplier, and operational metrics for actionable insights

- 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐋𝐞𝐚𝐧, 𝐒𝐢𝐱 𝐒𝐢𝐠𝐦𝐚, 𝐚𝐧𝐝 𝐊𝐚𝐢𝐳𝐞𝐧 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 𝐢𝐧𝐢𝐭𝐢𝐚𝐭𝐢𝐯𝐞𝐬

Qualifications & Eligibility

Notably broad on engineering discipline (mechanical, industrial, aerospace, CS, IT, electronics all qualify) — the real differentiator is data tool exposure, not a specific engineering major.

- 𝐁𝐚𝐜𝐡𝐞𝐥𝐨𝐫'𝐬 𝐢𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 (Mechanical, Industrial, Production, Aerospace, CS, IT, Electronics, or related)

- 𝐅𝐫𝐞𝐬𝐡 𝐠𝐫𝐚𝐝𝐮𝐚𝐭𝐞 𝐨𝐫 𝐮𝐩 𝐭𝐨 𝟐 𝐲𝐞𝐚𝐫𝐬 𝐨𝐟 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞

- 𝐁𝐚𝐬𝐢𝐜 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐨𝐟 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐜𝐨𝐧𝐜𝐞𝐩𝐭𝐬

- 𝐄𝐱𝐩𝐨𝐬𝐮𝐫𝐞 𝐭𝐨 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐭𝐨𝐨𝐥𝐬 𝐚𝐧𝐝/𝐨𝐫 𝐓𝐚𝐛𝐥𝐞𝐚𝐮 (academic, internship, or certification-based)

- 𝐏𝐫𝐨𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐢𝐧 𝐄𝐱𝐜𝐞𝐥 𝐚𝐧𝐝 𝐏𝐨𝐰𝐞𝐫𝐏𝐨𝐢𝐧𝐭

Skills Required

Core requirements are tool-exposure based (Excel, PowerPoint, basic Tableau/Microsoft tools); the preferred list signals where genuine differentiation happens for competitive candidates

- 𝐁𝐚𝐬𝐢𝐜 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐝𝐚𝐭𝐚 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠

- 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐄𝐱𝐜𝐞𝐥 𝐚𝐧𝐝 𝐏𝐨𝐰𝐞𝐫𝐏𝐨𝐢𝐧𝐭 𝐩𝐫𝐨𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲

- 𝐅𝐚𝐦𝐢𝐥𝐢𝐚𝐫𝐢𝐭𝐲 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐭𝐨𝐨𝐥𝐬 𝐚𝐧𝐝 𝐢𝐧𝐭𝐞𝐫𝐞𝐬𝐭 𝐢𝐧 𝐚𝐩𝐩𝐥𝐲𝐢𝐧𝐠 𝐭𝐡𝐞𝐦 to engineering/business processes

- Preferred: 𝐛𝐚𝐬𝐢𝐜 𝐒𝐐𝐋 𝐚𝐧𝐝 𝐏𝐲𝐭𝐡𝐨𝐧 𝐟𝐨𝐫 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬

- Preferred: 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝/𝐊𝐏𝐈/𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞, 𝐦𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠/𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐝𝐚𝐭𝐚 𝐞𝐱𝐩𝐨𝐬𝐮𝐫𝐞